Applied-AI glossary

Clear definitions of agentic AI, AI agents, orchestration, RAG and other key concepts for putting AI into production across your organization.

• What is an AI agent? — An AI agent is a system that perceives its context, decides the next step, uses tools and data, and executes actions to meet a goal with minimal human intervention.
• AI agent vs chatbot — A chatbot responds within a conversation; an AI agent also decides, uses tools and runs multi-step actions to complete a task.
• What is an Agentic OS? — An Agentic OS is a bespoke orchestration layer that connects an organization's processes, data and tools so AI agents do real work in production, under human control.
• What is an enterprise copilot? — An enterprise copilot is an AI assistant embedded in a team's tools that suggests, drafts or executes tasks while keeping the person in control of the decision.
• What is agent evaluation (evals)? — Evals are systematic tests that measure whether an AI agent meets its goal with the required quality and reliability before going to production.
• Fine-tuning vs RAG — Fine-tuning retrains a model with your data; RAG gives it access to your data when answering. You choose based on freshness, cost and control of information.
• What is AI governance? — AI governance is the set of rules, controls and responsibilities that ensure an organization's AI systems are traceable, supervised and auditable.
• What is human-in-the-loop? — Human-in-the-loop is a design in which a person reviews, approves or corrects an AI system's decisions at the points where human judgment matters.
• What is agentic AI? — Agentic AI is an approach in which AI systems plan, decide and execute actions autonomously to reach a goal, instead of only generating text.
• What is AI in production? — AI in production is an AI system integrated into an organization's real operation —with live data, human control and traceability— and not a prototype or demo.
• What is responsible AI? — Responsible AI is the design and use of AI systems in a safe, transparent way, aligned with the organization's rules and values.
• What is an LLM? — An LLM is an AI model trained on large volumes of text to understand and generate language, and the foundation of most agents and copilots.
• What is LLMOps / MLOps? — LLMOps is the set of practices to deploy, monitor and maintain language models in production reliably.
• What is MCP (Model Context Protocol)? — The Model Context Protocol (MCP) is an open standard that lets AI models connect in a uniform way to external tools, data and systems.
• What is agent orchestration? — Agent orchestration is the coordination of several specialized AI agents, directed by an orchestrator, to solve a complex task from end to end.
• What is an AI orchestrator? — An AI orchestrator is the component that decides which agents act, in what order and how their results are combined within an agentic system.
• What is RAG? — RAG is a technique that connects a language model to your own information sources so it answers with verifiable data instead of only with its training.
• What is the ROI of an AI project? — AI ROI is the net business value an AI system generates against its cost, measured with a metric agreed before starting.
• What is a multi-agent system? — A multi-agent system is a set of AI agents that collaborate, each with a role, to solve tasks that a single agent would not handle well.
• What is traceability in AI? — AI traceability is the ability to know which data, steps and decisions produced each result of an AI system.