Comprehensive AI and ML terminology dictionary. Clear definitions, business context, and practical examples for 65+ essential AI terms and concepts.
A method of comparing two versions of a webpage, email, or ad to determine which performs better based on measurable outcomes like clicks or conversions.
A method of comparing two versions of a web page, email, or other asset to determine which performs better by randomly splitting traffic between the two variants and measuring outcomes.
When an online shopper adds items to their shopping cart but leaves the website without completing the purchase, representing lost revenue that can be partially recovered through automated follow-up.
The process of re-engaging customers who have added items to an online shopping cart but left the website without completing the purchase, using automated follow-up communications to encourage conversion.
A set of predefined conditions that a deliverable must meet to be accepted by the project stakeholders, defining the boundaries of a user story or feature.
Security mechanisms that regulate who can view, use, or modify resources in a computing environment, ensuring only authorised users can access specific data and systems.
A B2B marketing strategy that concentrates resources on a defined set of target accounts, using personalised campaigns designed to engage each account based on their specific needs.
The proportion of correct predictions among total predictions. A basic classification metric that can be misleading for imbalanced datasets.
The proportion of correct predictions among total predictions, a basic metric for classification model evaluation.
A step that an automated workflow performs, such as sending an email, updating a database, calling an API, or creating a document.
An on-demand analysis created to answer a specific business question, rather than being part of a regular reporting cycle.
A prolonged, targeted cyberattack in which an intruder gains access to a network and remains undetected for an extended period, often to steal sensitive data or monitor activity.
An iterative approach to project management and software development that emphasises flexibility, collaboration, customer feedback, and delivering working results in short cycles.
Autonomous AI systems that can perceive their environment, make decisions, and take actions to achieve specific goals. Unlike simple chatbots, agents can use tools, access external data, and execute multi-step tasks independently.
The challenge of ensuring AI systems behave according to human intentions and values. Critical for making powerful AI systems safe, helpful, and beneficial.
The principles and practices ensuring AI systems are developed and used in ways that are fair, transparent, and beneficial.
An organisation's preparedness to successfully adopt and benefit from AI, including data, technology, talent, and cultural factors.
A comprehensive plan defining how an organisation will adopt and leverage AI to achieve business objectives.
A cloud-based platform combining spreadsheet simplicity with database power, enabling flexible data organisation and automation.
AWS's fully managed service for accessing foundation models from multiple providers including Anthropic, Meta, and Amazon through a unified API.
The process of identifying unusual patterns, data points, or observations that deviate significantly from expected behaviour, using statistical methods or machine learning algorithms.
The AI safety company behind the Claude family of AI assistants, known for emphasising responsible AI development and constitutional AI.
A set of laws, regulations, and procedures designed to prevent criminals from disguising illegally obtained funds as legitimate income.
A set of protocols and tools that allows different software applications to communicate with each other. In AI, APIs enable applications to access AI model capabilities without running the models locally.
Technical documentation describing how to effectively use and integrate with an API.
A server that acts as an entry point for APIs, handling request routing, authentication, rate limiting, and other cross-cutting concerns.
A server that acts as a single entry point for a set of backend APIs or microservices, handling request routing, authentication, rate limiting, and protocol translation.
Practices and technologies for protecting APIs from threats including unauthorised access, data breaches, and abuse.
Testing APIs to ensure they function correctly, handle errors gracefully, perform adequately, and are secure.
Strategies for managing changes to APIs while maintaining backwards compatibility for existing clients.
Prudential standards issued by the Australian Prudential Regulation Authority that set requirements for financial institutions regarding risk management, governance, and capital adequacy.
The mandatory reporting obligations that Australian companies, financial services providers, and market participants must fulfil with the Australian Securities and Investments Commission.
Automation that runs on a user's workstation and works alongside humans, triggered and supervised by the user.
A technique in neural networks that allows models to focus on relevant parts of the input when producing output. It's the core innovation behind transformer models and modern LLMs.
The process of assigning credit to different marketing touchpoints along the customer journey to understand which channels and campaigns drive conversions.
The process of determining which marketing channels, campaigns, or touchpoints deserve credit for driving a conversion or sale, using various models to distribute credit across the customer journey.
The time period after a marketing touchpoint during which a conversion is credited to that touchpoint, typically ranging from 1 to 90 days depending on the platform and business.
A chronological record of all activities, changes, and transactions within a system, providing evidence of who did what, when, and why.
The process of enhancing AI model capabilities by connecting them to external data sources, tools, or knowledge bases. RAG (Retrieval Augmented Generation) is a prime example.
The thirteen principles under the Privacy Act 1988 that regulate how Australian government agencies and organisations with annual turnover of more than $3 million handle personal information.
The process of verifying the identity of a user, device, or system attempting to access a resource.
The process of determining what actions or resources an authenticated user or system is permitted to access.
Automatically adjusting computing resources (servers, containers, or functions) based on current demand, adding capacity during peak loads and removing it during quiet periods.
Microsoft's framework for building multi-agent AI systems where multiple AI agents collaborate to solve complex tasks.
Tracking automation performance, health, and outcomes through dashboards, alerts, and analytics to ensure reliable operation.
The return on investment from automation initiatives, measuring the value delivered relative to the costs of implementation and operation.
Validating that automated processes work correctly through systematic testing before and after deployment.
A physically separate data centre within a cloud region with independent power, cooling, and networking, providing fault tolerance for cloud applications.
The average total time spent handling a customer interaction from start to finish, including talk time, hold time, and any after-call work required to resolve the enquiry.
The average dollar amount spent each time a customer places an order on an e-commerce website, calculated by dividing total revenue by the number of orders.
Amazon's managed service for accessing foundation models from multiple providers through a unified API.
Microsoft's hosting of OpenAI models on Azure, providing enterprise-grade security, compliance, and integration with Azure services.
Microsoft Azure's enterprise service for accessing OpenAI models with Azure security, compliance, and regional data residency.
A prioritised list of work items (features, enhancements, bugs, and tasks) that the team needs to complete, serving as the single source of truth for what needs to be built or done.
The ongoing process of reviewing, clarifying, estimating, and prioritising items in the product backlog to ensure they are ready for selection in upcoming sprints.
The primary algorithm used to train neural networks by calculating gradients and adjusting weights to minimise errors. It propagates error signals backward through the network.
The process of creating copies of data and systems so they can be restored in the event of data loss, corruption, hardware failure, cyberattack, or disaster.
The process of creating copies of data and systems so they can be restored in the event of data loss, corruption, hardware failure, or cyberattack such as ransomware.
The maximum rate of data transfer across a network connection, measured in bits per second (Mbps, Gbps), determining how much data can be transmitted at any given time.
Processing multiple items or transactions together as a group, typically scheduled for off-peak times.
Processing data in groups or batches at scheduled intervals rather than immediately as it arrives.
Processing multiple requests or data points together in a single operation rather than one at a time. This improves throughput and efficiency in AI systems.
Standardised tests used to evaluate and compare AI model performance across specific tasks or capabilities.
The practice of comparing an organisation's performance metrics, processes, or practices against industry standards, competitors, or best-in-class organisations to identify improvement opportunities.
The natural person or persons who ultimately own or control an entity, even if the legal ownership is held through intermediary structures such as trusts, nominees, or corporate chains.
Bidirectional Encoder Representations from Transformers - a landmark language model from Google that reads text in both directions to understand context.
Systematic errors in AI predictions caused by assumptions in the training data or algorithm. Can lead to unfair or inaccurate outputs for certain groups or scenarios.
Data synchronisation where changes in either connected system are reflected in the other, maintaining consistency in both directions.
Overseeing and coordinating software bots in an automation environment, including scheduling, monitoring, and maintenance.
The act of customers voluntarily promoting and recommending a brand to others based on genuine positive experiences, serving as organic, trusted marketing driven by satisfaction and loyalty.
The holistic perception a customer forms through every interaction with a brand, encompassing visual identity, communications, products, services, and emotional connections across all touchpoints.
The practice of tracking mentions of a brand, products, competitors, and industry terms across digital channels to manage reputation, identify opportunities, and respond to customer feedback.
A cyberattack method that uses trial and error to guess passwords, encryption keys, or login credentials by systematically attempting every possible combination until the correct one is found.
A visual programming platform for building full-featured web applications without writing code.
A graphical representation of work remaining versus time in a sprint or project, showing actual progress against the ideal completion rate.
A form submitted to the Australian Taxation Office to report and pay business tax obligations including GST, PAYG instalments, PAYG withholding, and other tax liabilities.
A documented justification for an AI investment, including expected benefits, costs, risks, and strategic alignment.
The process of creating systems of prevention and recovery to deal with potential threats to an organisation, ensuring that critical business functions can continue during and after a disaster.
A sophisticated email scam targeting businesses that make wire transfers or handle sensitive data, where attackers impersonate executives or trusted partners to trick employees into transferring funds or revealing confidential information.
Technologies and practices for collecting, integrating, analysing, and presenting business data. Enables data-driven decision making through dashboards, reports, and analytics.
Technologies and practices for collecting, integrating, analysing, and presenting business data to support better decision-making.
The strategies, technologies, and practices used to collect, integrate, analyse, and present business data to support better decision-making across an organisation.
Using technology to automate repeatable business processes, reducing manual effort and increasing consistency. Broader than RPA, encompassing workflow systems and integrations.
A discipline for designing, executing, monitoring, and improving business processes to achieve organisational goals.
A payment option allowing customers to purchase products immediately and pay in instalments over time, typically interest-free, offered through services like Afterpay, Zip, and Klarna.
A dedicated team or function that provides governance, standards, expertise, and support for enterprise automation initiatives.
Storing copies of data or computed results in faster storage to reduce latency and load on the original data source.
Storing copies of frequently accessed data in a faster storage layer so future requests for that data can be served more quickly, reducing load on primary systems and improving performance.
The planning, execution, tracking, and analysis of marketing campaigns across multiple channels, often coordinated through dedicated software platforms.
The process of determining team bandwidth available for upcoming work periods, accounting for leave, meetings, and other commitments to set realistic delivery expectations.
A centralised team or framework that provides leadership, best practices, and governance for automation initiatives across an organisation.
A prompting technique that encourages AI models to show their reasoning step-by-step, leading to more accurate results on complex problems.
The structured approach to transitioning individuals, teams, and organisations to a desired future state. Critical for AI adoption where people's roles and processes change.
The structured approach to transitioning individuals, teams, and organisations from current state to a desired future state.
The structured approach to transitioning individuals, teams, and organisations from a current state to a desired future state, managing the people side of change to achieve business outcomes.
A formal proposal to modify project scope, schedule, budget, or deliverables after the initial plan has been approved.
Using AI-powered or rule-based chatbots to engage website visitors, qualify leads, answer questions, and guide prospects through the marketing funnel in real time.
The use of automated conversational agents to handle customer enquiries, provide information, and resolve issues through text or voice-based interactions without human agent involvement.
The process of improving the e-commerce checkout experience to reduce abandonment and increase the percentage of shoppers who complete their purchase.
A lightweight, open-source embedding database designed for AI applications, popular for its simplicity and ease of use.
An open-source embedding database designed to be simple to use, particularly popular for development and prototyping AI applications.
Breaking large documents or texts into smaller, manageable pieces for processing. Critical for RAG systems where documents must fit within context windows.
The process of analysing customer departure patterns to understand why customers leave, identify at-risk customers, and develop strategies to improve retention.
Using AI and analytics to identify customers likely to stop using a product or service, enabling proactive retention efforts.
The use of data analysis and machine learning to identify customers who are likely to stop using a product or service, enabling businesses to intervene proactively before the customer leaves.
Continuous Integration and Continuous Delivery/Deployment -- automated practices that enable frequent, reliable code changes through automated building, testing, and deployment pipelines.
Business users who create applications or automations using no-code/low-code platforms without traditional programming skills.
Enabling non-IT employees to build applications and automations using low-code/no-code tools with appropriate governance.
Anthropic's family of AI assistants, known for being helpful, harmless, and honest. Claude models excel at analysis, writing, coding, and following nuanced instructions.
An omnichannel retail service where customers purchase products online and pick them up at a physical store location, combining the convenience of online shopping with immediate availability.
A systematic process where customer feedback is collected, analysed, acted upon, and the results communicated back to the customer, ensuring that feedback leads to tangible improvements.
The delivery of computing services including servers, storage, databases, networking, and software over the internet, enabling businesses to use technology without owning physical infrastructure.
The practice of reducing cloud computing costs while maintaining or improving performance, through right-sizing, reserved instances, spot instances, and eliminating waste.
The process of moving applications, data, and IT infrastructure from on-premises environments or legacy systems to cloud computing platforms.
An approach to building and running applications that fully exploits the advantages of cloud computing, using containers, microservices, serverless, and DevOps practices.
A geographic area containing data centres where cloud providers offer services, affecting data residency, latency, and compliance.
The set of policies, technologies, and controls protecting cloud-based data, applications, and infrastructure from threats, unauthorised access, and compliance violations.
The set of policies, technologies, and controls deployed to protect data, applications, and infrastructure hosted in cloud computing environments from threats, unauthorised access, and data breaches.
A formal document that outlines an organisation's values, expected behaviours, ethical standards, and rules that guide the actions and decisions of employees, directors, and contractors.
An enterprise-focused AI company providing language models, embeddings, and search capabilities through a developer-friendly API.
An enterprise AI company providing LLMs optimised for business applications, with strong focus on retrieval, classification, and embeddings.
An analytical technique that groups users or customers into cohorts based on shared characteristics or experiences within a defined time period, then tracks their behaviour over time.
The systematic process of evaluating competitor online stores, pricing, product ranges, marketing strategies, and customer experience to identify opportunities and inform strategic decisions.
The systematic process of receiving, recording, investigating, and resolving customer complaints to restore satisfaction, identify systemic issues, and improve products and services.
The output text generated by a language model in response to a prompt. Also refers to the API endpoint type for generating text continuations.
The use of technology to automate compliance-related processes, including monitoring, reporting, documentation, and control testing, reducing manual effort and human error.
The shared values, attitudes, and behaviours within an organisation that prioritise ethical conduct, regulatory adherence, and accountability as integral to how the business operates.
Structured sets of guidelines, policies, and best practices that organisations follow to meet regulatory requirements, industry standards, and security obligations.
The ongoing process of observing, checking, and evaluating whether an organisation's activities, policies, and controls remain in line with applicable laws, regulations, and internal standards.
AI that enables computers to interpret and understand visual information from images and videos. Powers image recognition, object detection, and visual inspection.
The field of AI that enables computers to interpret and understand visual information from images and videos.
Changes in the relationship between input features and target variables over time, causing model predictions to become less accurate.
A situation where an individual's personal interests, relationships, or outside activities could compromise their ability to act impartially and in the best interests of the organisation they serve.
A table showing predicted vs actual classifications, revealing true positives, false positives, true negatives, and false negatives. Essential for understanding model error patterns.
A table showing the counts of correct and incorrect predictions for each class, revealing detailed model performance.
A pre-built integration component that enables applications to communicate with external systems, handling authentication and data formatting.
The body of law and regulation that safeguards buyers of goods and services from unfair business practices, defective products, and misleading conduct.
Packaging an application and its dependencies into a standardised unit (container) that runs consistently across any computing environment, enabling portable and efficient deployment.
A geographically distributed network of servers that delivers web content to users from the nearest location, reducing latency and improving load times for websites and applications.
Software that enables creating, managing, and publishing digital content without requiring technical coding skills, serving as the foundation for websites and digital experiences.
Using technology to automate the planning, creation, distribution, and measurement of content marketing activities across channels and audience segments.
The maximum amount of text (measured in tokens) that an LLM can process in a single request. This includes both the input prompt and the generated output.
The obligation for ASX-listed entities to immediately inform the market of any information that a reasonable person would expect to have a material effect on the price or value of their securities.
An ongoing effort to improve products, services, or processes through incremental enhancements and breakthrough innovations, rooted in the belief that there is always room for improvement.
AI-powered technology that records, transcribes, and analyses customer conversations across channels to extract insights about customer sentiment, agent performance, and business opportunities.
The use of messaging apps, chatbots, and voice assistants to facilitate shopping and purchasing experiences through natural conversational interactions rather than traditional e-commerce interfaces.
The systematic process of increasing the percentage of website visitors who take a desired action, such as making a purchase, filling out a form, or booking a consultation.
The percentage of visitors or recipients who complete a desired action, calculated by dividing the number of conversions by the total number of visitors and multiplying by 100.
The percentage of users or visitors who complete a desired action (such as making a purchase, filling out a form, or signing up) out of the total number who could have done so.
Neural network architecture designed for processing grid-like data such as images. Uses convolution operations to automatically learn spatial features and patterns.
The system of rules, practices, and processes by which a company is directed and controlled, balancing the interests of stakeholders including shareholders, management, customers, and the community.
A Python framework for orchestrating role-playing AI agents that work together as a crew to accomplish complex tasks.
The longest sequence of dependent tasks in a project that determines the minimum time required to complete the project - any delay on the critical path directly delays the project.
The practice of recommending complementary or related products to customers based on their current selection, increasing order value by suggesting items that enhance the primary purchase.
The total cost of acquiring a new customer, including all marketing and sales expenses divided by the number of new customers acquired during a specific period.
A group of selected customers who meet regularly with a company to provide strategic feedback, share insights about industry trends, and influence product direction and business strategy.
A business strategy that puts the customer's interests at the centre of all decisions, and the resulting behaviour where satisfied customers actively recommend and promote the brand to others.
The practice of collecting, analysing, and interpreting data about customer behaviour, preferences, and interactions to improve customer acquisition, retention, and lifetime value.
The rate at which customers stop doing business with an organisation over a given period, calculated as the percentage of customers lost relative to the total customer base.
Software that collects and unifies customer data from multiple sources into a single, persistent customer profile, making it available for marketing and analytics tools.
A software system that collects and unifies customer data from multiple sources into a single, persistent customer profile, making it available to other systems for marketing, sales, and service activities.
A metric that measures how much effort a customer had to exert to get their issue resolved, question answered, or transaction completed, based on the principle that reducing effort increases loyalty.
The overall perception customers have of their interactions with a company. AI and automation can dramatically improve CX through personalisation, speed, and consistency.
The discipline of understanding, designing, and optimising every interaction a customer has with a business to deliver experiences that meet or exceed expectations and drive business outcomes.
The quantitative measurements used to evaluate, track, and improve the quality of customer experiences across all touchpoints and stages of the customer relationship.
A systematic process of collecting customer feedback, analysing it for insights, implementing improvements based on findings, and communicating changes back to customers.
A composite metric that combines multiple data signals to assess the overall health of a customer relationship, predicting the likelihood of retention, expansion, or churn.
The complete experience a customer has with a company, from initial awareness through purchase and beyond.
The analysis of every interaction a customer has with a business across all touchpoints and channels to understand the complete experience and identify improvement opportunities.
The process of visualising every interaction a customer has with a business from initial awareness through purchase and beyond, identifying touchpoints, emotions, and opportunities.
The process of visualising and documenting every interaction a customer has with a business from initial awareness through purchase, use, and beyond, identifying pain points and opportunities at each stage.
The complete progression of stages a customer goes through in their relationship with a business, from initial awareness through acquisition, engagement, retention, and potentially advocacy or departure.
The predicted total revenue a customer will generate throughout their entire relationship with a business.
A prediction of the total net revenue a business can expect to generate from a customer throughout the entire duration of their relationship.
The total net profit a business expects to earn from a customer over the entire duration of their relationship, critical for e-commerce businesses to understand acquisition cost limits.
The total revenue a business can expect from a single customer account throughout their entire relationship, used to guide marketing spend and customer acquisition strategies.
The process of guiding new customers through initial setup, training, and engagement to ensure they quickly achieve value from a product or service.
A system for managing all interactions with current and potential customers, centralising contact information, sales pipeline data, and communication history in one platform.
The strategies and activities focused on keeping existing customers coming back to make repeat purchases, reducing churn and maximising customer lifetime value.
The ability of a business to keep its existing customers over time, measured as the percentage of customers who remain active compared to those who were customers at the start of a period.
A metric that measures how satisfied customers are with a specific interaction, product, or service, typically captured through a survey asking customers to rate their satisfaction on a scale.
The practice of dividing customers into groups based on common characteristics to enable targeted marketing and personalised experiences.
Dividing customers into groups based on shared characteristics such as demographics, behaviour, purchase history, or needs to enable targeted marketing and personalised experiences.
The practice of dividing a customer base into distinct groups based on shared characteristics, behaviours, needs, or value, enabling targeted strategies for each segment.
Dividing e-commerce customers into groups based on shared characteristics such as purchase behaviour, demographics, lifetime value, or engagement level, to enable targeted marketing.
Automating customer support through chatbots, self-service portals, ticket routing, and AI-assisted agent tools.
A proactive business function focused on ensuring customers achieve their desired outcomes through the use of a product or service, driving retention, expansion, and advocacy.
A comprehensive organisational initiative to fundamentally redesign and improve the customer experience across all touchpoints, processes, and technologies to deliver superior value and differentiation.
Insurance policies designed to protect businesses from the financial impact of cyber incidents such as data breaches, ransomware attacks, business interruption, and regulatory penalties.
A brief daily team meeting (typically 15 minutes) where each member shares what they completed, what they plan to do, and any blockers preventing progress.
The practice of scanning dark web forums, marketplaces, and data dumps to detect if an organisation's credentials, data, or intellectual property have been compromised and are being traded or sold.
A visual display of key metrics and data points that provides at-a-glance understanding of business performance.
A visual display of the most important information needed to achieve one or more objectives, consolidated and arranged on a single screen so the information can be monitored at a glance.
Techniques for artificially increasing training data by creating modified versions of existing data.
An incident where sensitive, protected, or confidential data is accessed, disclosed, or stolen by an unauthorised party, whether through cyberattack, human error, or system vulnerability.
The structured process an organisation follows when personal or sensitive data is accessed, disclosed, or lost without authorisation, including containment, assessment, notification, and remediation.
A centralised inventory of data assets with metadata, enabling discovery, understanding, and governance of organisational data.
The process of detecting and correcting errors, inconsistencies, and inaccuracies in datasets to improve data quality.
Changes in the statistical properties of input data over time that can degrade machine learning model performance.
The process of enhancing existing data by supplementing it with additional information from external or internal sources to improve its accuracy, completeness, and analytical value.
The framework of policies, processes, and standards for managing data assets. Ensures data is accurate, secure, compliant, and used appropriately across the organisation.
The overall management of data availability, usability, integrity, and security across an organisation, including policies, processes, and standards for data handling.
The process of annotating data with labels or tags that machine learning models can learn from.
The process of adding annotations or tags to data to create training datasets for supervised learning. Labels tell the model what output to predict for each input.
A storage repository holding vast amounts of raw data in native format until needed. Unlike warehouses, lakes store unstructured and semi-structured data without predefined schemas.
A centralised repository that stores raw data in its native format, enabling flexible analysis and machine learning workloads.
A centralised storage repository that holds vast amounts of raw data in its native format until it is needed for analysis, supporting structured, semi-structured, and unstructured data.
An architecture combining data lake flexibility with data warehouse reliability and performance.
Tracking the origin, movement, and transformation of data throughout its lifecycle in an organisation.
The ability to track data from its origin through transformations to its final use, showing the complete data journey.
The ability to read, understand, create, and communicate data as information, including the skills to work with data, analyse it, and use it for decision-making.
Technologies and processes that detect and prevent the unauthorised transmission, leakage, or theft of sensitive data from an organisation through monitoring, detection, and blocking.
The process of creating a visual or mathematical representation of data structures, relationships, and rules to organise and manage data effectively for analysis and application development.
An automated sequence of data processing steps that moves and transforms data from sources to destinations. Essential for keeping AI systems and analytics fed with fresh data.
An automated series of processes that extract data from source systems, transform it according to business rules, and load it into a destination system for analysis and reporting.
Protecting personal and sensitive information from unauthorised access, use, and disclosure.
The measure of data fitness for its intended purpose. High-quality data is accurate, complete, consistent, timely, and valid. Critical for AI systems that learn from data.
The degree to which data is accurate, complete, consistent, timely, and fit for its intended use.
The measure of how well data serves its intended purpose, assessed across dimensions including accuracy, completeness, consistency, timeliness, validity, and uniqueness.
Protecting data from unauthorised access, corruption, or theft through technical and administrative controls.
The concept that data is subject to the laws and governance of the country where it is stored or processed, relevant for Australian businesses choosing cloud regions and data storage locations.
The concept that digital data is subject to the laws and governance structures of the country in which it is collected or stored, requiring organisations to manage data according to local regulations.
The principle that data is subject to the laws and governance structures of the country in which it is collected or stored, giving nations jurisdiction over data within their borders.
The practice of combining data, visualisations, and narrative to communicate insights in a compelling and memorable way that drives understanding and action.
The process of maintaining consistency between data stored in different systems or locations.
Keeping data consistent across multiple systems by automatically copying and updating data when changes occur. Essential for multi-system architectures.
Converting data from one format, structure, or value system to another. Essential for integration when systems use different data models or formats.
The process of converting data from one format or structure to another to meet the requirements of target systems or analysis.
The process of checking data against rules and constraints to ensure accuracy, completeness, and consistency.
The graphical representation of data and information using charts, graphs, maps, and other visual elements to communicate patterns, trends, and insights clearly and effectively.
A centralised repository that stores integrated data from multiple sources for reporting and analysis. Optimised for query performance rather than transaction processing.
A centralised repository optimised for analytical queries, storing structured data from multiple sources for business intelligence and reporting.
A centralised repository of structured data from multiple sources that is optimised for analysis, reporting, and business intelligence rather than transactional processing.
A marketing approach that uses customer data and analytics to inform decisions about targeting, messaging, channel selection, and budget allocation rather than relying on intuition.
A unified analytics platform combining data engineering, data science, and machine learning on a lakehouse architecture.
A transformation tool that enables analytics engineers to transform data using SQL, with software engineering best practices.
A Distributed Denial of Service attack that overwhelms a target server, service, or network with a flood of internet traffic from multiple sources, making it unavailable to legitimate users.
The component of a transformer model that generates output sequences. GPT-style models are "decoder-only" architectures optimised for text generation.
Machine learning using neural networks with multiple layers. Enables automatic feature learning and powers modern AI breakthroughs in vision, language, and more.
A shared agreement within the team that defines all the conditions a work item must meet before it can be considered complete and potentially releasable.
A formal framework that specifies who within an organisation has the authority to make decisions, approve expenditure, enter contracts, and commit resources, and within what limits.
Using historical data, market trends, and statistical models to predict future customer demand for products, enabling better inventory planning and purchasing decisions.
The process of identifying, tracking, and managing the relationships between tasks, teams, or systems where one element relies on another for completion or input.
The analysis of historical data to understand what has happened in the business, using techniques such as aggregation, summarisation, and visualisation to describe past performance.
A set of practices combining software development (Dev) and IT operations (Ops) to shorten the development lifecycle, deliver features faster, and improve collaboration between teams.
The analysis that goes beyond describing what happened to explain why it happened, using techniques such as drill-down analysis, correlation analysis, and root cause investigation.
AI models that generate images by gradually removing noise from random patterns. Powers tools like DALL-E, Midjourney, and Stable Diffusion.
An integrated technology platform that manages, delivers, and optimises digital experiences across websites, mobile apps, portals, and other digital channels throughout the customer lifecycle.
Integrating digital technology into all areas of business, fundamentally changing how organisations operate and deliver value. AI and automation are key enablers.
The integration of digital technology into all areas of business, fundamentally changing how organisations operate and deliver value.
A software application that securely stores payment information and enables fast, contactless payments online and in-store, such as Apple Pay, Google Pay, and PayPal.
The number of features or dimensions in an embedding vector. Higher dimensionality can capture more nuance but requires more storage and compute.
The set of policies, tools, and procedures for recovering technology infrastructure and systems after a disaster, ensuring business continuity in the event of catastrophic failure.
The practice of protecting Domain Name System infrastructure from attacks and abuse, including DNS hijacking, spoofing, and cache poisoning, to ensure reliable and secure domain name resolution.
A platform for containerising applications, essential for deploying AI models consistently across different environments.
A platform for building, running, and distributing containerised applications, enabling developers to package applications with all dependencies into portable containers.
Using AI and software to automatically create, process, extract data from, and manage documents without manual intervention.
Automatically creating, processing, routing, and managing documents using templates, data extraction, and workflow rules.
The system that translates human-readable domain names (like example.com.au) into IP addresses that computers use to identify and communicate with each other on the internet.
An automated series of pre-written emails or messages sent on a schedule or triggered by specific user actions, designed to nurture leads or guide customers through a journey.
A retail fulfilment method where the store does not hold inventory but instead transfers customer orders directly to a supplier who ships products to the customer.
The comprehensive investigation and analysis undertaken before entering into a business transaction, agreement, or relationship to assess risks, verify facts, and ensure informed decision-making.
Website or email content that automatically changes based on user data, behaviour, preferences, or context, delivering personalised experiences to different visitors or recipients.
An automated pricing strategy where product prices are adjusted in real time based on factors such as demand, competition, inventory levels, time of day, and customer segments.
A cloud-hosted database service where the provider manages provisioning, patching, backups, scaling, and high availability, letting teams focus on application development rather than database administration.
The percentage of website visitors who complete a purchase on an e-commerce site, calculated by dividing the number of transactions by the total number of sessions.
Automated email campaigns targeting e-commerce customers based on their shopping behaviour, including browse abandonment, cart recovery, post-purchase follow-up, and win-back sequences.
Tailoring the shopping experience to individual customers based on their behaviour, preferences, demographics, and purchase history, including personalised recommendations, content, and offers.
Processing data closer to the source of data generation rather than in a centralised data centre, reducing latency and bandwidth usage for time-sensitive applications.
Automated sending, sorting, and responding to emails based on triggers, schedules, or content analysis. Includes marketing sequences, transactional emails, and inbox management.
Automatically sending, sorting, responding to, or processing emails based on triggers, rules, or AI-driven understanding.
The ability of marketing emails to successfully reach recipients inboxes rather than being filtered to spam, bounced, or blocked by email service providers.
Software designed for creating, sending, and tracking email campaigns at scale, with features for list management, automation, templates, and performance analytics.
Analytics capabilities integrated directly into business applications, workflows, and products, allowing users to access insights within the tools they already use without switching to separate BI platforms.
Numerical vector representations of text, images, or other data that capture semantic meaning. Similar items have similar embeddings, enabling semantic search.
The use of AI and data analysis techniques to detect, measure, and interpret customer emotions from interactions, feedback, and behaviour patterns to improve customer experience decisions.
The component of a transformer that processes input text into internal representations. BERT-style models are "encoder-only" and excel at understanding tasks.
The process of converting readable data (plaintext) into an unreadable format (ciphertext) using mathematical algorithms, ensuring only authorised parties with the correct key can access the information.
Converting data into a coded format readable only by authorised parties with the decryption key, protecting confidentiality at rest and in transit across cloud infrastructure.
Security software deployed on devices (laptops, desktops, mobiles, servers) to protect against malware, ransomware, and other threats at the device level.
Adherence to environmental laws, regulations, standards, and policies that govern how businesses manage their impact on the natural environment.
A large body of work that can be broken down into smaller user stories, representing a significant feature or capability that typically spans multiple sprints to complete.
The process of transferring a customer issue or request to a higher level of authority, expertise, or priority when it cannot be resolved at the current level of support.
The process of predicting the effort, time, or cost required to complete a piece of work, using techniques such as story points, planning poker, or analogous estimation.
A data integration process that extracts data from sources, transforms it to fit operational needs, and loads it into a destination system like a data warehouse.
A data integration process that extracts data from sources, transforms it for analysis, and loads it into a destination system.
A data integration process that extracts data from source systems, transforms it into a suitable format and structure, and loads it into a destination system such as a data warehouse.
Quantitative measures used to assess AI model performance, such as accuracy, precision, recall, F1 score, and perplexity.
Automation triggered by real-time events rather than schedules. Responds immediately when something happens - a form submission, database change, or API call.
Automations triggered in response to specific events or changes in systems, enabling real-time reactive workflows.
Managing situations where automated processes encounter unexpected conditions or errors that prevent normal completion.
Managing cases where automated processes encounter unexpected conditions, errors, or situations outside normal parameters.
A visual representation of the complete experience a person has with an organisation, capturing actions, thoughts, emotions, and pain points across every stage and touchpoint of their interaction.
The harmonic mean of precision and recall, providing a single metric that balances both. Useful when you need good performance on both false positives and false negatives.
The harmonic mean of precision and recall, providing a single metric that balances both concerns.
Adherence to Australian workplace laws governed by the Fair Work Act 2009, covering minimum employment conditions, awards, enterprise agreements, and employee rights.
Facebook AI Similarity Search, a library for efficient similarity search and clustering of dense vectors at scale.
The process of creating and selecting input variables (features) for machine learning models. Good features capture relevant patterns and improve model performance.
A technique where models learn to perform tasks from just a few examples provided in the prompt, without additional training.
A legal obligation to act in the best interest of another party, requiring the highest standard of care, loyalty, and good faith, commonly owed by directors, trustees, and professional advisers.
The use of data analysis techniques to examine financial data, forecast financial performance, optimise financial decisions, and provide insights for strategic planning.
Adapting a pre-trained model to a specific task or domain by training it further on specialised data. Creates a new model variant.
A network security device or software that monitors and controls incoming and outgoing network traffic based on predetermined security rules, creating a barrier between trusted and untrusted networks.
The percentage of customer enquiries or issues that are resolved during the customer's first interaction with the support team, without requiring follow-up or additional contacts.
Data collected directly from your own customers and audience through owned channels like your website, app, CRM, and purchase transactions, as opposed to data purchased from external sources.
An open-source visual tool for building LLM flows and AI agents using a drag-and-drop interface built on LangChain.
Large AI models trained on broad data that can be adapted to many downstream tasks. GPT-4, Claude, and BERT are examples that serve as the foundation for specific applications.
Large AI models trained on broad data that can be adapted to a wide range of downstream tasks.
The proactive measures, controls, and processes implemented by an organisation to detect, deter, and prevent fraudulent activities including financial fraud, identity fraud, and internal misconduct.
A customer experience design philosophy focused on removing unnecessary obstacles, delays, and effort from every interaction, making it as easy as possible for customers to achieve their goals.
The complete process of receiving, processing, picking, packing, and shipping customer orders from warehouse to delivery, including returns handling.
An LLM capability to output structured requests to external functions or APIs, enabling AI to take actions like searching databases or executing code.
The examination of a multi-step process (such as a sales or conversion funnel) to identify where users drop off at each stage and optimise the overall conversion rate.
The framework of policies, processes, and accountability structures that guide responsible AI development and use.
A bar chart that illustrates a project schedule, showing tasks along the vertical axis and time along the horizontal axis, with bars representing the start, duration, and end of each task.
The European Union regulation on data protection and privacy that applies to organisations worldwide if they process personal data of EU residents.
AI systems that create new content - text, images, code, audio, or video. Includes LLMs like GPT and Claude, and image generators like DALL-E and Midjourney.
AI systems that can create new content including text, images, audio, video, and code.
The analysis of data that includes geographic or spatial components, using mapping, location intelligence, and spatial analysis to reveal patterns and insights tied to physical locations.
A free web analytics platform by Google that tracks and reports website traffic, user behaviour, and conversion data for websites and mobile apps.
Google Cloud's unified ML platform providing access to Google's AI models and tools for building AI applications.
Google Cloud's unified AI platform for building, deploying, and scaling ML models, including access to Gemini and PaLM models.
An integrated approach to managing corporate governance, risk management, and regulatory compliance as a unified discipline rather than separate siloed functions.
OpenAI's family of language models that generate human-like text. GPT-4 is currently the most capable version, excelling at reasoning, coding, and analysis.
The optimisation algorithm used to train neural networks by iteratively adjusting weights to minimise the loss function.
A Python library for quickly creating web interfaces for machine learning models, particularly popular for AI demos.
A Python library for quickly creating web interfaces for machine learning models with automatic UI generation.
A query language for APIs that lets clients request exactly the data they need. Alternative to REST that reduces over-fetching and enables flexible data retrieval.
A query language for APIs that allows clients to request exactly the data they need, developed by Facebook.
The accurate, verified labels or outcomes used to train and evaluate machine learning models.
Connecting AI model outputs to factual, verified information sources to reduce hallucinations and improve accuracy.
A marketing approach focused on rapid experimentation across channels and product development to identify the most efficient ways to grow a business, typically used by startups and scale-ups.
Safety mechanisms and constraints implemented to prevent AI systems from producing harmful, inappropriate, or off-topic outputs.
When an AI model generates plausible-sounding but factually incorrect or fabricated information. A major challenge in deploying AI for business.
An e-commerce architecture where the front-end presentation layer is decoupled from the back-end commerce functionality, connected through APIs for maximum flexibility and customisation.
A visual representation of user interaction data on a webpage, using colour gradients to show where users click, scroll, move their mouse, or spend time on a page.
A centralised system and team that manages and resolves customer or internal user support requests through a structured ticketing process.
System design ensuring services remain operational for a very high percentage of time (99.9%+), minimising downtime through redundancy, failover, and fault tolerance.
A decoy system or resource deliberately designed to attract cyberattackers, enabling security teams to detect, deflect, and study attack methods without risking real assets.
The leading platform for sharing and deploying machine learning models, datasets, and applications. Known for the Transformers library.
The leading open-source AI platform providing model hosting, datasets, and the Transformers library for machine learning development.
Automation design that includes human review, approval, or intervention points for handling exceptions or validating AI decisions.
A computing environment that combines on-premises infrastructure with public cloud services, allowing data and applications to move between private and public environments.
A project management approach that combines elements of Agile and traditional (waterfall) methodologies, adapting practices from each to suit the specific needs and constraints of the project.
An organisation-wide strategy to automate as many business and IT processes as possible using multiple technologies including AI, RPA, process mining, and low-code platforms.
A business-driven approach to rapidly identify, vet, and automate as many business processes as possible using multiple technologies.
Configuration settings that control the training process, such as learning rate, batch size, and number of epochs. Set before training begins.
A statistical method used to determine whether there is enough evidence in a sample of data to support a specific claim about a population or process.
The framework of policies and technologies for managing digital identities, ensuring the right people have appropriate access to technology resources across an organisation.
AI capability to identify and classify objects, people, text, and other content within images. Powers applications from photo organisation to quality inspection.
An external company that helps organisations plan, build, and deploy AI solutions.
The ability of LLMs to learn and adapt their behaviour based on examples and instructions provided in the prompt, without model updates.
The process of identifying, analysing, and responding to events that disrupt normal business operations or pose risks to the organisation, with the goal of restoring normal operations and preventing recurrence.
The organised approach to addressing and managing the aftermath of a security breach or cyberattack, with the goal of limiting damage, reducing recovery time, and preventing future incidents.
Using a trained model to make predictions or generate outputs on new data. This is the "runtime" phase of AI, as opposed to training.
A marketing strategy that involves partnering with individuals who have significant online followings to promote products or services, leveraging their credibility and audience reach.
The framework of policies, processes, and standards that govern how information is created, stored, used, protected, and disposed of across an organisation to ensure quality, security, and compliance.
A cloud computing model providing virtualised computing resources over the internet, including virtual machines, storage, and networking that businesses manage themselves.
Managing and provisioning computing infrastructure through machine-readable configuration files rather than manual processes, enabling version control and automated deployment of infrastructure.
A security risk originating from within an organisation, including employees, contractors, or business partners who misuse their authorised access to harm the organisation's data, systems, or operations.
Fine-tuning a model on examples of following instructions to improve its ability to understand and execute user requests.
Combining RPA with AI capabilities like machine learning, NLP, and computer vision to automate processes that require judgment, learning, or understanding unstructured data.
The combination of RPA with AI capabilities like machine learning and NLP to automate complex processes requiring judgement.
The processes, policies, and procedures implemented by an organisation to ensure the integrity of financial and accounting information, promote accountability, and prevent fraud.
A security system that monitors network traffic or system activities for malicious behaviour or policy violations and generates alerts when suspicious activity is detected.
The process of keeping product stock levels accurate and consistent across all sales channels, warehouses, and systems in real time to prevent overselling and stockouts.
A network of physical devices embedded with sensors, software, and connectivity enabling them to collect and exchange data, powering applications from smart agriculture to industrial automation.
Cloud-based platforms that connect applications, data, and processes across cloud and on-premises environments. Examples include Zapier, Make, and Workato.
Integration Platform as a Service, cloud-based platforms for connecting applications and data across cloud and on-premise systems.
The international standard for information security management systems (ISMS), providing a framework for establishing, implementing, maintaining, and continually improving information security.
A single cycle of development within an iterative process, where a working increment is planned, built, tested, and reviewed before the next cycle begins.
A lightweight data format for storing and exchanging data. Human-readable and easy to parse, JSON is the standard format for API requests and responses.
JavaScript Object Notation, a lightweight data interchange format that is easy for humans to read and machines to parse.
A compact, URL-safe token format for securely transmitting claims between parties. Used for authentication and authorisation in web applications and APIs.
A Japanese philosophy and practice of continuous incremental improvement in all aspects of an organisation, where everyone from the CEO to frontline workers contributes to identifying and implementing small improvements daily.
A visual workflow management method that uses boards and cards to visualise work, limit work in progress, and maximise flow efficiency through continuous delivery.
The process of creating, storing, distributing, rotating, and revoking cryptographic keys used for encrypting data, a critical component of data security.
A measurable value that demonstrates how effectively an organisation is achieving its key business objectives, used to evaluate success at reaching targets.
A type of surveillance software or hardware that records every keystroke made on a computer or mobile device, often used by attackers to capture passwords, credit card numbers, and sensitive information.
The process of verifying the identity of clients and assessing potential risks of illegal intentions in the business relationship, required under anti-money laundering regulations.
A structured repository of information that AI systems can query. In RAG systems, this typically contains company documents, FAQs, and domain-specific content.
A centralised, searchable repository of information including articles, guides, FAQs, and documentation that helps customers and support agents find answers to common questions.
A network of entities (people, places, concepts) and their relationships, enabling AI to reason about connections and context.
Quantifiable measures used to evaluate success in meeting objectives. For AI projects, KPIs track both technical performance and business outcomes.
Measurable values that demonstrate how effectively an organisation is achieving key business objectives.
An open-source container orchestration platform for automating deployment, scaling, and management of containerised applications.
An open-source container orchestration platform that automates deployment, scaling, and management of containerised applications across clusters of servers.
The process of improving landing page elements to increase the conversion rate, ensuring visitors take the desired action such as filling a form, making a purchase, or booking a call.
A popular open-source framework for building LLM applications. Provides abstractions for chains, agents, memory, and integrations with various AI services.
A visual IDE for building and deploying LangChain applications through a flow-based interface with Python extensibility.
A platform from LangChain for debugging, testing, evaluating, and monitoring LLM applications.
The time delay between sending a request and receiving a response from an AI system. Critical for real-time applications.
The time delay between a user action (like clicking a link) and the system response, measured in milliseconds. Lower latency means faster, more responsive applications.
A free resource or incentive offered to prospects in exchange for their contact information, such as an ebook, template, calculator, checklist, or free trial.
A methodology for ranking prospects based on their perceived value and likelihood to convert, often enhanced by AI.
A methodology for ranking prospects based on their perceived value to the business, using demographic fit and behavioural engagement data to prioritise sales follow-up.
A methodology focused on maximising customer value while minimising waste, originally derived from the Toyota Production System and now applied across industries including software development and business operations.
The process of tracking, maintaining, and renewing all business licences, permits, registrations, and certifications required for an organisation to legally operate.
A real-time text-based communication channel on websites and apps that connects customers with human support agents for immediate assistance, often enhanced with AI-powered features.
Meta's family of open-source large language models. Llama 2 and 3 offer strong performance that can be self-hosted without API costs.
A data framework for building LLM applications, specialising in connecting custom data to language models. Excellent for RAG applications.
AI models trained on vast amounts of text that can understand and generate human language. GPT-4, Claude, and Llama are leading examples.
Distributing incoming network traffic across multiple servers to ensure no single server becomes overwhelmed, improving application availability, reliability, and performance.
An efficient fine-tuning technique that trains only a small number of additional parameters, dramatically reducing compute and storage requirements.
Development platforms that minimise hand-coding through visual interfaces while still allowing code customisation when needed. Bridges no-code and traditional development.
A structured marketing programme that rewards customers for repeat purchases and engagement, typically through points, tiers, discounts, or exclusive benefits to encourage ongoing business.
A structured marketing strategy that rewards customers for repeat business, encouraging ongoing engagement and purchases through points, discounts, exclusive benefits, or tiered membership levels.
A visual automation platform for connecting apps and designing complex workflows, formerly known as Integromat.
Malicious software designed to damage, disrupt, or gain unauthorised access to computer systems, including viruses, worms, trojans, ransomware, spyware, and adware.
A cyberattack where the attacker secretly intercepts and potentially alters communications between two parties who believe they are communicating directly with each other.
Legal obligations requiring certain individuals or organisations to report specific events, conditions, or information to designated authorities within prescribed timeframes.
The application of artificial intelligence technologies to marketing activities including content creation, audience targeting, campaign optimisation, and customer insights.
The practice of measuring, managing, and analysing marketing performance data to maximise effectiveness and optimise return on investment across channels and campaigns.
The practice of measuring, managing, and analysing marketing performance data to maximise marketing effectiveness and optimise return on marketing investment.
Software and strategies that automate marketing tasks including email campaigns, social media, lead nurturing, and customer journey orchestration.
Software and strategies that automate marketing tasks including email campaigns, lead nurturing, social media, and campaign analytics.
Technology that automates repetitive marketing tasks such as email campaigns, social media posting, lead nurturing, and ad management, allowing teams to scale personalised marketing efforts.
A model representing the stages potential customers pass through from initial awareness to final purchase, used to guide marketing strategy and measure conversion at each stage.
A statistical analysis technique that quantifies the impact of various marketing channels on sales and other outcomes, helping businesses optimise budget allocation across channels.
A lead that has been assessed by marketing as having sufficient engagement and fit criteria to warrant sales team follow-up, based on defined scoring thresholds.
The measurement of return on marketing investment for e-commerce businesses, calculating the profit generated relative to the total cost of marketing activities.
The collection of software tools and platforms a business uses to plan, execute, and measure marketing activities, typically including CRM, email, analytics, advertising, and content management tools.
Connecting an e-commerce business with third-party marketplaces like Amazon, eBay, and Catch to list products, sync inventory, and manage orders across multiple selling platforms.
Systems that allow AI to retain and recall information across conversations. Can be short-term (within session) or long-term (across sessions).
A component that stores messages sent between applications, enabling asynchronous communication and decoupling between services.
A communication method in distributed systems where messages are sent between components through a queue, enabling asynchronous processing and decoupling of services.
Data that describes other data, providing context about structure, meaning, origin, and usage.
Brief, intent-driven moments when customers turn to a device to act on a need - to know, go, do, or buy something - representing critical opportunities to shape decisions and preferences.
An architectural style where applications are composed of small, independent services that communicate over network protocols.
An architectural approach where an application is built as a collection of small, independent services that communicate over APIs, each responsible for a specific business capability.
Software that connects different applications or systems, handling communication, data transformation, and integration logic between components.
Software that sits between applications, providing common services like messaging, authentication, and data transformation.
A significant point or event in a project that marks the completion of a major phase, deliverable, or achievement, used to track overall project progress.
The simplest version of a product that can be released to early users to test a core hypothesis, gather feedback, and validate demand before investing in full development.
A French AI company known for efficient, high-performance open-weight language models that compete with much larger models.
A French AI company known for efficient, high-performance open-weight models that compete with larger proprietary models.
Neural network architecture using multiple specialised "expert" subnetworks with a gating mechanism that routes inputs to the most relevant experts, enabling larger models with efficient compute.
An open-source platform for managing the machine learning lifecycle, including experimentation, reproducibility, and deployment.
The buying and selling of products and services through mobile devices such as smartphones and tablets, including mobile-optimised websites, apps, and mobile payment systems.
A trained AI system that can make predictions or generate outputs. Models encode learned patterns from training data in their parameters.
The infrastructure and processes for deploying trained models to make predictions in production environments.
Obligations under the Modern Slavery Act 2018 (Cth) requiring large businesses to report on modern slavery risks in their operations and supply chains and actions taken to address those risks.
Collecting, analysing, and acting on data about system health and performance through metrics, logs, and traces to ensure reliable applications.
Architectures where multiple AI agents collaborate, each with specialised roles, to accomplish complex tasks through coordination.
Using services from multiple cloud providers (such as AWS, Azure, and Google Cloud) rather than relying on a single provider, for flexibility, redundancy, or best-of-breed service selection.
A security method requiring users to provide two or more verification factors to gain access to a system, combining something they know (password), have (phone), or are (fingerprint).
AI models that can process and generate multiple types of data - text, images, audio, and video. GPT-4V and Gemini are multi-modal.
AI systems that can process and generate multiple types of data such as text, images, audio, and video.
A testing method that simultaneously examines multiple page elements and their combinations to determine which combination produces the best results, more complex than A/B testing.
An open-source, self-hostable workflow automation platform with both visual builder and code capabilities.
NLP technique that identifies and classifies named entities in text - people, organisations, locations, dates, monetary values, and other specific information.
The branch of AI focused on enabling computers to understand, interpret, and generate human language. Powers chatbots, translation, sentiment analysis, and more.
The field of AI focused on enabling computers to understand, interpret, and generate human language.
The ability to ask questions about data using everyday language rather than writing SQL or other technical query languages, enabled by AI that translates natural language into database queries.
A metric measuring customer loyalty and satisfaction based on likelihood to recommend a company to others.
A customer loyalty metric based on the question "How likely are you to recommend us?" scored 0-10, categorising respondents as Promoters (9-10), Passives (7-8), or Detractors (0-6).
A customer loyalty metric that measures how likely customers are to recommend a business to others, calculated from responses to the question "On a scale of 0-10, how likely are you to recommend us?"
A metric that measures the percentage of recurring revenue retained from existing customers over a period, including the effects of upgrades, downgrades, and churn, indicating how well a business grows within its customer base.
The practices, policies, and technologies designed to protect the integrity, confidentiality, and accessibility of computer networks and the data they carry.
The practice of dividing a computer network into smaller, isolated subnetworks to improve security, performance, and manageability by limiting the spread of threats and controlling traffic flow between segments.
A computing system inspired by biological brains, consisting of interconnected nodes (neurons) that process information in layers.
The field of AI focused on enabling computers to understand, interpret, and generate human language.
Platforms that allow building applications and automations without writing code, using visual interfaces and pre-built components.
A data breach that is likely to result in serious harm to affected individuals and must be reported to the OAIC and notified to the affected individuals under the Privacy Act 1988.
An all-in-one workspace combining notes, docs, wikis, databases, and project management with AI capabilities.
An authorisation framework that lets users grant limited access to their accounts on one service to another service, without sharing passwords.
Computer vision task that identifies and locates objects within images or video, drawing bounding boxes around each detected item and classifying what it is.
A data storage architecture managing data as objects with unique identifiers and metadata, ideal for storing unstructured data like images, videos, and backups at scale.
A goal-setting framework that defines qualitative objectives and the quantitative key results that measure progress toward each objective, used to align and track organisational priorities.
A category of data processing that enables fast, multi-dimensional analysis of large volumes of data, allowing users to slice, dice, drill down, and pivot data for business intelligence.
A tool for running large language models locally on your own computer, making LLMs accessible without cloud APIs.
A customer experience approach that provides seamless, consistent interactions across all channels (phone, email, chat, social, in-person), with context preserved as customers move between channels.
A unified commerce approach that provides customers with a seamless shopping experience across all channels -- online, mobile, in-store, social, and marketplace -- with shared data and consistent service.
A marketing approach that provides a seamless, consistent customer experience across all channels and touchpoints, with each channel aware of interactions on other channels.
The AI research company behind GPT models, ChatGPT, and DALL-E. A leader in large language model development.
The API and developer platform from OpenAI providing access to GPT models, DALL-E, Whisper, and embedding models for building AI applications.
A standard, language-agnostic format for describing REST APIs, enabling documentation, code generation, and testing.
The use of data analysis to improve day-to-day business operations, optimise processes, monitor performance in real time, and drive operational efficiency.
The ratio of output to input in business operations, often improved through AI automation and optimisation.
Coordinating multiple AI components, models, or agents to work together in a workflow. Managing data flow, error handling, and sequencing.
Software that manages the entire order lifecycle from placement to delivery, coordinating orders across multiple sales channels, inventory locations, and fulfilment methods.
When a model learns training data too well, including noise and outliers, leading to poor performance on new data.
The learned values (weights and biases) in a neural network that determine its behavior. LLMs have billions of parameters.
A software application that securely stores, generates, and manages passwords for multiple accounts, enabling users to maintain strong, unique passwords for every service without memorising them.
The process of identifying, acquiring, testing, and installing software updates (patches) to fix security vulnerabilities, bugs, and improve functionality across all systems and applications.
An advertising model where businesses pay a fee each time their ad is clicked, most commonly used in search engine and social media advertising platforms.
A technology service that processes online payment transactions by securely transmitting payment information between the customer, merchant, and financial institutions.
A simulated cyberattack conducted by security professionals to identify vulnerabilities in systems, networks, and applications before malicious attackers can exploit them.
Tailoring marketing messages, content, products, and experiences to individual users based on their data, preferences, behaviour, and context to increase relevance and engagement.
The practice of tailoring products, services, content, and communications to individual customers based on their preferences, behaviours, and characteristics.
A PostgreSQL extension that adds vector similarity search capabilities, enabling AI applications on existing PostgreSQL infrastructure.
A social engineering attack where criminals send deceptive emails, messages, or create fake websites designed to trick people into revealing sensitive information like passwords, financial data, or personal details.
A small-scale preliminary project used to evaluate feasibility, test approaches, and learn before committing to full implementation.
A popular managed vector database optimised for AI applications. Known for ease of use and scalability.
A sequence of data processing or AI steps connected together, where each step's output feeds into the next.
A cloud computing model that provides a platform for developing, deploying, and managing applications without the complexity of maintaining the underlying infrastructure.
The hardware and software system where retail transactions are completed in-store, processing payments, tracking inventory, and connecting with e-commerce systems for omnichannel operations.
The systematic process of creating, approving, distributing, implementing, reviewing, and updating organisational policies to ensure they remain current, effective, and compliant with regulatory requirements.
A popular API development platform for designing, testing, documenting, and monitoring APIs.
Microsoft's cloud-based automation platform for creating workflows across Microsoft 365 and third-party applications.
Initial training phase where models learn general patterns from large datasets. Pre-trained models can then be fine-tuned for specific tasks with much less data.
Of all positive predictions, what proportion was actually positive. High precision means few false positives - when the model says "yes," it's usually right.
The proportion of true positive predictions among all positive predictions, measuring how reliable positive predictions are.
Using statistical algorithms, machine learning, and historical data to forecast future outcomes such as customer behaviour, churn risk, purchase likelihood, and campaign performance.
The use of statistical models, machine learning algorithms, and data mining techniques to analyse current and historical data to make predictions about future outcomes.
The most advanced form of analytics that not only predicts what is likely to happen but recommends specific actions to take, using optimisation, simulation, and decision science.
The approach a business uses to set product prices based on costs, competition, perceived value, market positioning, and customer willingness to pay.
An approach to systems engineering that embeds privacy protections into the design and architecture of IT systems and business practices from the outset, rather than adding them as an afterthought.
A systematic assessment of how a project, system, or initiative will handle personal information, identifying potential privacy risks and recommending measures to mitigate them.
A cyberattack technique where an attacker gains elevated access to resources that are normally protected, moving from a lower-privilege account to higher-privilege access such as administrator or root.
A support strategy that anticipates customer issues and reaches out to help before customers need to contact support, preventing problems rather than reacting to them.
Evaluating business processes to determine their suitability and priority for automation.
Analysing event logs from IT systems to discover, monitor, and improve business processes. Reveals how processes actually work versus how they're supposed to work.
Data-driven analysis of business processes using event logs to discover, monitor, and improve actual process execution.
Offering multiple products together as a package at a combined price typically lower than buying each item separately, encouraging larger purchases and increasing average order value.
A structured database of all products available for sale, including descriptions, images, pricing, variants, categories, and specifications used across all sales channels.
A structured data file containing product information formatted for distribution to advertising platforms, comparison sites, and marketplaces like Google Shopping, Meta, and affiliate networks.
The Scrum role responsible for maximising the value of the product by managing and prioritising the product backlog based on stakeholder needs and business strategy.
The process of improving e-commerce product pages to increase conversion rates through better images, descriptions, reviews, pricing presentation, and user experience.
AI-powered software that analyses customer behaviour and product data to suggest relevant products to shoppers, powering "You may also like" and "Customers also bought" features.
Insurance that protects professionals and their businesses against claims of negligence, errors, or omissions arising from the professional services or advice they provide.
The automated buying and selling of digital advertising using algorithms and real-time bidding, replacing manual ad placement with data-driven, instant decision-making.
A formal document that authorises a project, defines its objectives, scope, stakeholders, and constraints, and gives the project manager authority to apply organisational resources.
A formal document that authorises a project, defines its objectives, scope, stakeholders, and high-level requirements, serving as the project foundation.
A formal document defining project objectives, scope, timeline, resources, budget, risks, and communication plan, serving as the roadmap for execution.
The input text or instructions given to an AI model to elicit a response. Quality prompts dramatically improve output quality.
The practice of designing and optimising prompts to get better results from AI models. Combines art and science.
A messaging pattern where senders (publishers) send messages to topics without knowledge of receivers (subscribers), who receive messages by subscribing to topics.
An even more efficient fine-tuning technique that combines quantisation with LoRA, enabling fine-tuning of large models on consumer hardware.
The systematic process of ensuring deliverables meet defined quality standards through planned activities, testing, and reviews throughout the project lifecycle.
Reducing the precision of model weights (e.g., from 32-bit to 4-bit) to decrease memory usage and increase speed with minimal quality loss.
A request sent to an AI system or database to retrieve information or generate a response. In RAG, queries trigger retrieval from the knowledge base.
The systems and strategies used to organise, prioritise, and manage customer waiting lines across service channels, minimising wait times and optimising the customer experience during service delivery.
A responsibility assignment chart that defines who is Responsible, Accountable, Consulted, and Informed for each task or deliverable in a project.
A technique that enhances LLM responses by first retrieving relevant information from a knowledge base, then using it to generate accurate, grounded answers.
Malicious software that encrypts a victim organisation files and demands a ransom payment (typically in cryptocurrency) in exchange for the decryption key to restore access.
Controlling the number of requests a client can make to an API within a specified time period to prevent abuse and ensure fair usage.
The process of analysing data as it is generated or received, providing immediate insights and enabling instant decision-making rather than waiting for batch processing.
Data that is delivered and processed immediately or with minimal delay as it is generated.
Processing data or transactions immediately as they occur, enabling instant responses and up-to-date information.
Of all actual positives, what proportion did the model identify. High recall means few false negatives - the model finds most of the positive cases.
The proportion of actual positive cases that were correctly identified, measuring how completely positives are found.
The systematic practice of maintaining business records for specified periods to meet legal, regulatory, and operational requirements before secure disposal.
Neural network designed to process sequential data by maintaining internal state. Used for time series, text, and other sequential tasks before transformers became dominant.
An open-source, in-memory data store used as a database, cache, message broker, and queue, known for sub-millisecond response times and versatile data structures.
A marketing strategy that encourages existing customers to recommend a business to new prospects, typically through structured programs offering incentives for successful referrals.
A structured incentive system that rewards existing customers for recommending products to new customers, leveraging word-of-mouth for cost-effective customer acquisition.
A statistical method that examines the relationship between a dependent variable and one or more independent variables, used for prediction and understanding drivers.
The process of identifying, assessing, and implementing changes to business operations, policies, and systems in response to new or amended laws, regulations, and standards.
The process of ensuring that an organisation adheres to all relevant laws, regulations, standards, and guidelines that govern its industry and operations.
A machine learning paradigm where agents learn by interacting with an environment, receiving rewards or penalties for actions. Used in robotics, games, and optimisation.
Machine learning where an agent learns to make decisions by taking actions and receiving rewards or penalties.
The percentage of customers who return to make a second or subsequent purchase, a key indicator of customer loyalty and product-market fit in e-commerce.
A platform for running machine learning models in the cloud via API, making it easy to deploy open-source models without managing infrastructure.
The process of assigning and managing available resources - including people, budget, equipment, and time - across projects and activities to maximise efficiency and achieve objectives.
An architectural style for web APIs using standard HTTP methods. The most common way to build and consume web services, enabling system-to-system communication.
An architectural style for web APIs using HTTP methods to perform operations on resources, the most common approach for modern web services.
Showing targeted ads to people who have previously visited your website or engaged with your content, reminding them of your brand and encouraging them to return and convert.
The measurement and analysis of how well a business retains its customers over time, including identifying the factors that drive loyalty and reduce attrition.
A low-code platform for building internal tools and admin panels by connecting to databases and APIs.
The process of finding and fetching relevant information from a database or knowledge base in response to a query.
A regular team meeting at the end of each sprint or project phase where the team reflects on what went well, what could be improved, and commits to specific improvement actions.
A metric measuring the revenue generated for every dollar spent on advertising, used to evaluate the effectiveness and profitability of e-commerce advertising campaigns.
The system and workflow for handling product returns including return authorisation, shipping, inspection, refund processing, and inventory restocking.
A systematic process of identifying, analysing, and evaluating cybersecurity risks to an organisation, determining the likelihood and impact of potential threats, and prioritising mitigation efforts.
A structured approach to identifying, assessing, managing, and monitoring risks across an organisation, typically aligned with standards such as ISO 31000 or AS/NZS ISO 31000.
A document that records identified project risks, their likelihood and impact assessment, mitigation strategies, owners, and current status throughout the project lifecycle.
A technique to fine-tune AI models using human preferences, making outputs more helpful, harmless, and aligned with human values.
A strategic visual plan that communicates the direction and planned evolution of a product, project, or business initiative over time, showing themes, priorities, and expected timelines.
Software robots that automate repetitive, rule-based tasks by mimicking human interactions with digital systems. Works with existing applications without API integration.
Software robots that automate repetitive, rule-based tasks by mimicking human interactions with digital systems.
A measure of profitability that compares the gain from an investment to its cost. For AI projects, ROI considers cost savings, revenue increases, and implementation costs.
The process of calculating and evaluating the return on investment for business activities, projects, or spending to determine their financial effectiveness.
The process of calculating return on investment by comparing the gains from an investment against its costs.
Software that executes business rules to automate decisions, separating decision logic from application code.
Automating sales tasks like lead assignment, follow-up sequences, proposal generation, and CRM updates to increase efficiency.
Providing sales teams with the content, tools, knowledge, and information they need to effectively engage buyers and close deals, bridging the gap between marketing and sales.
A visual representation of where prospects are in the sales process, from initial contact to closed deal.
The process of ensuring that a business does not engage in transactions or activities with individuals, entities, or countries subject to economic sanctions imposed by Australia, the United Nations, or other relevant jurisdictions.
The ability of a system or process to handle growing amounts of work or to be enlarged to accommodate growth.
Automation that runs at predetermined times rather than in response to events. Used for batch processing, reports, maintenance tasks, and regular synchronisation.
Automations triggered by time-based schedules rather than events, running at defined intervals or specific times.
The uncontrolled expansion of project scope without corresponding adjustments to time, budget, or resources, often occurring gradually through small, incremental additions.
An Agile framework for developing, delivering, and sustaining complex products through iterative sprints, with defined roles, events, and artefacts that enable empirical process control.
A servant-leader role in Scrum responsible for facilitating the Scrum process, removing impediments, and coaching the team to continuously improve.
Paid advertising on search engines like Google and Bing, where businesses bid on keywords to display ads in search results when users search for relevant terms.
A cloud-based architecture that combines network security functions (such as SWG, CASB, FWaaS, and ZTNA) with wide area networking capabilities (SD-WAN) to deliver secure access from any location.
A systematic evaluation of an organisation security posture, assessing the effectiveness of security controls, policies, and procedures against established standards or frameworks.
Educational programs designed to teach employees about cybersecurity threats, safe practices, and their role in protecting organisational data and systems from attack.
A centralised facility or team responsible for continuously monitoring, detecting, analysing, and responding to cybersecurity incidents using a combination of technology solutions and skilled analysts.
A category of security tools that combine incident response, orchestration, and automation capabilities to help security teams manage threats more efficiently by automating repetitive tasks and standardising response procedures.
The process of dividing a broad group into distinct subgroups based on shared characteristics, enabling targeted analysis, marketing, and service delivery.
An approach to business intelligence where business users can access, analyse, and visualise data independently without requiring technical assistance from IT or data teams.
A web-based platform that allows customers to find information, manage their accounts, resolve issues, and complete transactions independently without contacting a support agent.
Search that understands meaning and intent rather than just matching keywords. Uses embeddings to find conceptually similar content.
NLP technique that determines the emotional tone of text - positive, negative, or neutral. Used for analysing customer feedback, social media, and reviews.
The use of NLP to identify and extract subjective information, determining whether text expresses positive, negative, or neutral sentiment.
The use of natural language processing (NLP) and machine learning to identify, extract, and quantify subjective information from text data, determining whether the expressed opinion is positive, negative, or neutral.
Using tools and software to automate search engine optimisation tasks such as keyword tracking, site auditing, content optimisation, backlink monitoring, and reporting.
Optimising online store pages to rank higher in search engine results, driving organic traffic through keyword-optimised product pages, category pages, and content.
A cloud execution model where the cloud provider manages server infrastructure and dynamically allocates resources, charging only for actual compute time used rather than pre-provisioned capacity.
A detailed visual diagram that maps the complete service delivery process, showing customer actions, frontstage interactions, backstage processes, and support systems needed to deliver a customer experience.
A multidisciplinary approach to designing and improving services by considering the entire ecosystem of people, processes, technology, and physical elements that together create the customer experience.
A formal agreement between a service provider and customer that defines the expected level of service, including response times, resolution times, availability, and consequences for non-compliance.
The process of identifying and resolving customer service failures to restore customer satisfaction, with the goal of turning a negative experience into a positive one that strengthens the customer relationship.
Using software to automate shipping tasks such as carrier selection, rate comparison, label printing, tracking updates, and customer notifications in the e-commerce fulfilment process.
The virtual container on an e-commerce website where customers collect products they intend to purchase before proceeding to checkout and completing their order.
Security Information and Event Management -- a platform that collects, analyses, and correlates security data from across an organisation to detect threats and support incident investigation.
Finding items in a database that are most similar to a query, typically using vector distance calculations on embeddings.
An ATO reporting system that requires employers to report employee payroll information - including salaries, wages, PAYG withholding, and superannuation - directly to the ATO each time they run payroll.
The system of creating, organising, and tracking Stock Keeping Units -- unique identifiers assigned to each distinct product variant for inventory management and sales tracking.
A cloud-native data warehouse platform offering scalable storage and compute for analytics and AI workloads.
A compliance framework developed by the American Institute of CPAs (AICPA) that evaluates an organisation's controls related to security, availability, processing integrity, confidentiality, and privacy.
Selling products directly through social media platforms like Instagram, Facebook, TikTok, and Pinterest, allowing customers to discover and purchase without leaving the social app.
Psychological manipulation techniques used by attackers to trick people into making security mistakes, revealing confidential information, or granting unauthorised access to systems.
The practice of monitoring social media platforms and online channels for mentions, conversations, and sentiment about a brand, products, competitors, and industry topics to inform customer experience decisions.
The process of creating, scheduling, publishing, and analysing content across social media platforms, typically using dedicated tools to manage multiple channels from one interface.
The psychological phenomenon where people look to the actions and opinions of others to determine correct behaviour, used in marketing through reviews, testimonials, case studies, and usage statistics.
A software distribution model where applications are hosted in the cloud and accessed by users over the internet via a subscription, eliminating the need for local installation and maintenance.
A fixed-length iteration (typically 1-4 weeks) in Scrum during which a team works to complete a set of backlog items and deliver a potentially releasable product increment.
A concise statement describing the objective of a sprint, providing the team with shared purpose and flexibility in how they achieve it.
A collaborative Scrum event at the start of each sprint where the team selects backlog items, defines the sprint goal, and creates a plan for delivery.
A Scrum event at the end of each sprint where the team demonstrates completed work to stakeholders, gathers feedback, and discusses next steps.
Malicious software that secretly monitors and collects information about a user's activities, including browsing habits, login credentials, and personal data, and transmits it to a third party without consent.
The standard programming language for managing and querying relational databases, essential for extracting, manipulating, and analysing structured data.
Cryptographic protocols that encrypt data transmitted between web browsers and servers, ensuring secure communication indicated by the padlock icon and HTTPS in the browser address bar.
The systematic process of identifying, analysing, and engaging individuals or groups who have an interest in or influence over a project, to build support and manage expectations.
A determination that the result of an analysis or experiment is unlikely to have occurred by random chance alone, typically measured at a 95% confidence level.
A unit of measure for expressing the overall effort, complexity, and uncertainty of a user story, used for relative estimation in Agile teams.
Sending AI model output incrementally as it's generated rather than waiting for the complete response. Improves perceived latency.
A Python framework for quickly building and sharing web applications for machine learning and data science.
A Python framework for creating web applications and data dashboards quickly, popular for AI/ML demos and tools.
Data organised in a predefined format with clear schema, typically stored in databases with rows and columns.
An e-commerce model where customers pay recurring fees for regular delivery of products or access to services, creating predictable revenue and stronger customer relationships.
A machine learning approach where models learn from labelled training data. The algorithm learns to map inputs to known outputs, enabling predictions on new, unseen data.
Machine learning where models learn from labeled training data to predict outcomes for new data.
A cyberattack that targets an organisation by compromising a less-secure element in its supply chain, such as a software vendor, service provider, or hardware manufacturer, to gain access to the ultimate target.
Artificially generated data that mimics real data characteristics. Used when real data is scarce, sensitive, or expensive to obtain for AI training.
Artificially generated data that mimics real data characteristics while preserving privacy and enabling use cases where real data is scarce or sensitive.
The process of meeting all tax obligations accurately and on time, including income tax, GST, payroll tax, fringe benefits tax, and other federal and state tax requirements.
A parameter controlling randomness in AI outputs. Lower temperature (0-0.3) gives consistent, focused responses; higher (0.7-1.0) gives more creative, varied ones.
An open-source Infrastructure as Code tool for defining, provisioning, and managing cloud infrastructure using declarative configuration files across multiple cloud providers.
NLP task of assigning predefined categories to text. Used for spam detection, sentiment analysis, topic categorisation, and intent recognition.
An outsourced logistics service that handles warehousing, fulfilment, and shipping on behalf of e-commerce businesses, allowing them to focus on product and marketing.
The process of identifying, assessing, and managing the risks that arise from an organisation's relationships with external vendors, suppliers, contractors, and service providers.
Information about current and potential cyber threats that is collected, analysed, and used to make informed security decisions and proactively defend against attacks.
The process of creating, categorising, assigning, tracking, and resolving customer support requests (tickets) through a structured system that ensures nothing falls through the cracks.
A statistical technique for analysing data points collected over time to identify trends, seasonal patterns, and cyclical behaviours for forecasting.
The total elapsed time from when a customer first reports an issue to when it is fully resolved and the customer confirms satisfaction, measuring the end-to-end efficiency of the support process.
The time between starting an investment and realising measurable benefits. Critical for AI projects where stakeholders expect results within reasonable timeframes.
The duration between starting an initiative and realising measurable business value from it.
A time management technique that allocates a fixed period of time to a planned activity, after which the time expires and the activity ends regardless of whether it is fully completed.
The process of breaking text into smaller units (tokens) that AI models can process. Tokens might be words, subwords, or characters depending on the tokenizer.
The process of breaking text into smaller units (tokens) that AI models can process and understand.
The basic units of text that LLMs process. Roughly 1 token = 4 characters or 0.75 words in English. Both input and output are measured in tokens.
The complete cost of acquiring, deploying, and operating an AI system over its lifetime. Includes obvious costs like software and hidden costs like training and maintenance.
The complete cost of acquiring, operating, and maintaining a system over its entire lifecycle, including hidden costs.
Any point of interaction between a customer and a business, including direct contacts (phone, email, visit), digital interactions (website, app, social), and indirect exposures (advertising, reviews, word of mouth).
The process of teaching an AI model by exposing it to data and adjusting its parameters to minimise errors.
The management of mandatory training requirements to ensure all employees complete required training programs within prescribed timeframes, meeting regulatory, legal, and organisational obligations.
The dataset used to train machine learning models. Training data teaches the model patterns and relationships it will apply to new, unseen data.
Applying knowledge learned from one task to a different but related task. This allows models to achieve good performance with less training data and compute.
A technique where a model trained on one task is adapted for a different but related task.
The neural network architecture behind modern LLMs. Uses attention mechanisms to process sequences in parallel, enabling training on massive datasets.
An event that initiates an automated workflow or action. Common triggers include form submissions, schedule times, data changes, emails, and webhooks.
Marketing messages or actions automatically initiated by specific customer behaviours or events, such as a website visit, cart abandonment, birthday, or subscription renewal date.
Automation that runs independently on servers without human intervention, typically triggered by schedules or events.
A comprehensive, consolidated profile that aggregates all customer data from across systems, channels, and touchpoints into a single accessible record, providing a complete picture of each customer relationship.
Data without a predefined format or schema, such as text documents, images, audio, and video.
Machine learning where models find patterns in data without labelled examples. The algorithm discovers hidden structures, clusters, or relationships autonomously.
Machine learning where models find patterns in data without labeled examples or predefined outcomes.
The practice of encouraging customers to purchase a more expensive version or upgraded model of the product they are considering, increasing the transaction value.
The percentage of time a system, server, or service is operational and accessible, typically expressed as a percentage like 99.9% (three nines) representing maximum allowed downtime.
A specific scenario describing how AI will be used to solve a business problem or enable a capability.
The final testing phase where actual business users verify that a system meets their requirements and is fit for purpose in real-world scenarios.
The overall experience a person has when interacting with a product, system, or service, encompassing usability, accessibility, efficiency, and emotional response.
A short, simple description of a feature or requirement written from the perspective of the end user, following the format "As a [user], I want [action], so that [benefit]."
Content created by customers about a brand or product, including reviews, photos, videos, and social media posts, which serves as authentic social proof and marketing material.
A standardised method of adding tracking parameters to URLs so analytics tools can identify which campaigns, channels, and content drive traffic and conversions.
A list of numbers representing data in multi-dimensional space. In AI, vectors (embeddings) encode semantic meaning of text or other data.
A specialised database optimised for storing and searching vector embeddings. Essential for RAG and semantic search applications.
A measure of the amount of work a Scrum team completes during a sprint, typically measured in story points, used for sprint planning and capacity forecasting.
The process of evaluating and choosing AI technology providers, platforms, or implementation partners.
A logically isolated section of the public cloud where you launch resources in a virtual network you define, with control over IP addressing, subnets, routing, and security.
A technology that creates an encrypted tunnel between a device and a network, securing data transmission and enabling secure remote access to company resources over the internet.
A research methodology and program that captures customers' expectations, preferences, and aversions through systematic collection and analysis of customer feedback across all channels.
A systematic programme for collecting, analysing, and acting on employee feedback and insights, recognising that employee experience directly impacts the quality of customer experience delivered.
Technology creating secure, encrypted connections over the internet between users or networks and remote resources, protecting data in transit.
Automated assessment of systems, networks, and applications to identify known security vulnerabilities, misconfigurations, and weaknesses that could be exploited by attackers.
The psychological experience of waiting for service, which is influenced by factors such as certainty, engagement, fairness, and context, and often differs significantly from actual elapsed time.
Software that manages and optimises warehouse operations including receiving, putaway, picking, packing, shipping, and inventory tracking across one or more locations.
A traditional, sequential project management methodology where each phase (requirements, design, development, testing, deployment) must be completed before the next begins.
An open-source vector database that combines vector search with traditional filtering, designed for AI applications.
An open-source vector database designed for AI applications, featuring built-in vectorisation, semantic search, and hybrid search capabilities.
The collection, measurement, and analysis of website data to understand visitor behaviour, track performance metrics, and make data-driven decisions about website improvement.
The collection, measurement, analysis, and reporting of website data to understand and optimise web usage, user behaviour, and conversion performance.
A security solution monitoring and filtering HTTP/HTTPS traffic to web applications, protecting against SQL injection, cross-site scripting, DDoS, and other web attacks.
A security solution that filters, monitors, and blocks HTTP/HTTPS traffic to and from a web application, protecting against attacks such as SQL injection, cross-site scripting (XSS), and DDoS at the application layer.
An HTTP callback that sends real-time data when events occur. Instead of polling for changes, systems push notifications to your endpoint automatically.
An automated HTTP callback that sends real-time data between marketing tools when specific events occur, enabling instant communication between systems without polling.
The numerical values in neural networks that are learned during training. They determine how strongly inputs influence outputs.
An ML platform for experiment tracking, model management, and collaboration in machine learning projects.
A popular MLOps platform for experiment tracking, model visualisation, and team collaboration in machine learning projects.
Legal protections for individuals who report suspected misconduct, illegal activity, or dangers within an organisation, shielding them from retaliation and adverse consequences.
A feature allowing customers to save products for future reference, serving as a purchase intent signal and remarketing opportunity for e-commerce businesses.
A hierarchical decomposition of the total scope of work into smaller, manageable components, breaking down project deliverables into progressively more detailed levels.
The total amount of work that has been started but not yet completed at any given point in time, with WIP limits being a key technique for improving flow efficiency.
A defined sequence of automated tasks that accomplish a business process. AI workflows combine multiple AI and non-AI steps.
Software that executes and manages business workflows, routing tasks, handling approvals, and tracking progress through multi-step processes.
A reusable, pre-configured workflow pattern that can be customised for specific use cases, accelerating automation development.
The legal framework and practices that ensure the health, safety, and welfare of all people at work, governed in Australia primarily by the model Work Health and Safety Act adopted by most states and territories.
A no-code automation platform that connects apps and automates workflows through trigger-action integrations called Zaps.
A security model based on the principle of "never trust, always verify" where no user, device, or network is automatically trusted, and every access request must be authenticated and authorised.
A security framework requiring all users and devices to be authenticated, authorised, and continuously validated before accessing applications, regardless of network location.
Performing tasks without any examples in the prompt, relying solely on the model's pre-trained knowledge and the task description.