Glossary
The AI glossary
The key AI terms in plain language, explained from our own practice. Not a dictionary, but what a term means and why it matters for your business.
AI technique
Agentic workflow An agentic workflow is a process in which an AI agent, not a human, plans the steps, calls tools, checks intermediate results and continues until the goal is reached. AI agent An AI agent is software that pursues a goal on its own: it plans the steps, uses tools or systems, checks the result and adjusts course, without a human directing every step. Eval Evals are automated tests for AI features that measure how accurately, safely and stably they perform on a fixed set of representative examples. Fine-tuning Fine-tuning is training an existing language model further on your own examples, so it fits a specific task, tone or field better. Hallucination A hallucination is when a language model confidently gives information that is incorrect or made up, presented as if it were a fact. Human-in-the-loop Human-in-the-loop means a person reviews or approves an AI process at the right moments, so mistakes are caught before they do any harm. LLM (Large Language Model) An LLM is a large language model trained on enormous amounts of text, which lets it understand and generate language; it is the engine under tools like ChatGPT, Claude and Gemini. MCP (Model Context Protocol) MCP is an open standard that lets AI models connect to external tools, data and systems in a uniform way, like a USB port for AI. Prompt engineering Prompt engineering is carefully formulating the instruction to an AI model, so it reliably produces the desired result. RAG (Retrieval-Augmented Generation) RAG lets a language model first retrieve the right documents from your own sources and base its answer on those, so it draws on your knowledge instead of only its training.
Strategy & implementation
AI Act The AI Act is the European law that sets rules for developing and using AI, with stricter requirements the more high-risk an application is. AI audit An AI audit is a focused review of your processes and data that maps where AI saves you the most time or errors, and what it takes to get there. AI implementation partner An AI implementation partner is an agency that does not just advise on AI but actually builds it, connects it to your systems, and keeps it running in your day-to-day processes. AIOS (AI Operating System) An AIOS is an AI layer that sits on top of your existing systems, reads data from all of them at once, and runs processes that affect the whole organisation, not just the individual employee.
Approach & collaboration
AI literacy AI literacy is your employees’ ability to understand AI, use it sensibly, and assess the results critically; since the AI Act it is also a legal obligation. AI workshop An AI workshop is a hands-on session in which your team learns what AI can and cannot do and applies it directly to their own work, so the knowledge sticks instead of evaporating. Proof of Concept (PoC) A proof of concept is a small, fast version of an AI solution that proves the idea works on real data, before you invest in a full build.
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