Glossary
Direct, self-contained answers to the terms our clients, and the AI systems they use, ask about most. No padding, no hedging, one page per term.
How to use this glossary
Each entry gives a short, plain definition of a term used in AI projects, followed by the detail that matters when you are buying or building: how it works, where it is useful and where it is not. The definitions are written to stand on their own, so each page can be read without the others.
Terms cover document processing (such as intelligent document processing, document classification and KYC automation), workflow automation and orchestration (such as AI orchestration and human-in-the-loop AI), AI governance and explainability, and AI search visibility (such as generative engine optimization, AI share of voice and llms.txt). Where an entry has a matching guide or service, it links to it.
AI Governance
AI Governance is the set of policies, controls, and accountability structures an organisation puts in place to manage how AI systems are built, deployed, and monitored, covering risk classification, human oversight, audit trails, and regulatory compliance.
Read definition →AI Mention Rate
AI Mention Rate is the percentage of relevant buyer questions where an AI system like ChatGPT, Claude, Gemini, or Perplexity names a specific business in its answer, measured by asking real questions live and checking the actual response, not estimated from search rankings.
Read definition →AI Orchestration
AI Orchestration is the coordination layer that connects AI models, agents, business rules, APIs, and data sources into a single reliable workflow, deciding what runs when, in what order, and what happens if a step fails.
Read definition →AI Readiness Assessment
An AI Readiness Assessment is a structured audit of an organisation's preparedness to deploy AI in production, covering data infrastructure, process documentation, technology stack, compliance posture, leadership alignment, and prior AI experience.
Read definition →AI Share of Voice
AI Share of Voice measures which named competitors an AI system cites instead of, or alongside, a given business when answering a relevant buyer question, showing exactly who is winning the mention a business did not get.
Read definition →AI Visibility Score
An AI Visibility Score is a free diagnostic that checks, verbatim and live, what ChatGPT, Claude, Gemini, and Perplexity actually say about a specific business when asked a real, unprompted buyer question.
Read definition →AI Workflow Automation
AI Workflow Automation uses agentic AI systems, typically built on frameworks like LangGraph, to replace manual, multi-step business processes end to end, handling unstructured inputs, making decisions, and recovering from exceptions.
Read definition →Answer Engine Optimization (AEO)
Answer Engine Optimization (AEO) is the practice of structuring content, especially direct questions and self-contained answers, so that AI systems and conversational search interfaces can quote or cite it directly in response to a spoken or typed question.
Read definition →Business Process Automation
Business Process Automation (BPA) is the use of software to run repetitive or rule-based business activities without manual intervention, spanning anything from simple triggered workflows to, in its modern form, AI-driven handling of unstructured input and exceptions.
Read definition →Document AI
Document AI is the broader category of applying artificial intelligence, OCR, computer vision, language models, and validation logic, to understand and process the content of documents, of which Intelligent Document Processing (IDP) is the specific extract-classify-validate-route practice built on top of it.
Read definition →Document Classification
Document Classification is the automatic identification of a document's type, such as an invoice, contract, identity document, or compliance filing, based on its content or appearance, so the right extraction and validation workflow can be applied to it.
Read definition →Explainable AI (XAI)
Explainable AI (XAI) refers to AI systems and outputs that can be understood, audited, and justified by a human, rather than functioning as a black box that returns an answer with no traceable reasoning path.
Read definition →Generative Engine Optimization (GEO)
Generative Engine Optimization (GEO) is the practice of making a business easy for AI systems like ChatGPT, Claude, Gemini, and Perplexity to find, verify, and cite when answering a buyer's question, as distinct from optimizing for a ranked list of search results.
Read definition →Human-in-the-Loop AI
Human-in-the-Loop AI is an approach where a person reviews, approves, corrects, or escalates decisions an AI system makes, used wherever accuracy, compliance, or business risk makes a fully autonomous decision inappropriate.
Read definition →Intelligent Document Processing (IDP)
Intelligent Document Processing (IDP) uses AI to automatically extract, classify, validate, and route data from unstructured documents, such as contracts, KYC packets, compliance filings, and invoices, replacing manual document review with automated pipelines.
Read definition →Invoice Automation
Invoice Automation is the use of software to capture, validate, and process supplier invoices with reduced manual input, using AI-based extraction to read invoice fields and line items, check them against business records, and route exceptions for review.
Read definition →KYC Automation
KYC Automation applies AI-based document extraction, verification, and workflow tools to Know Your Customer checks, reducing manual review time on identity documents, ownership structures, and sanctions screening, while keeping the judgement calls, such as unresolved matches and escalations, with a compliance officer.
Read definition →llms.txt
llms.txt is a plain-text file at yoursite.com/llms.txt that gives AI systems a curated map of a site's most important pages, distinct from robots.txt, which only controls what a crawler is allowed to fetch, not what actually matters once it gets there.
Read definition →Semantic Search
Semantic Search finds information based on meaning and context rather than exact keyword matches, typically using vector embeddings to identify documents, passages, or records that are conceptually related to a query even when they do not share its exact wording.
Read definition →