Glossary
AI terms, plainly explained.
Clear, concise definitions of the concepts that show up everywhere in AI — RAG, knowledge bases, workflow automation, agents, MCP, and more. Updated as the field evolves.
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Retrieval-Augmented Generation (RAG)
RAG (Retrieval-Augmented Generation) is an AI technique that retrieves relevant information from a knowledge source and uses it to ground the model's response — producing answers backed by your own documents instead of relying only on what the model memorized during training.
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AI Knowledge Base
An AI knowledge base is a searchable index of your company's documents, databases, and data sources that an AI model can query in natural language — turning static content into an interactive, citable resource.
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Workflow Automation
Workflow automation is the use of software to execute a series of tasks across multiple apps without human intervention — replacing repetitive manual work with reliable, repeatable processes.
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AI Agent
An AI agent is an autonomous software system that uses a language model to reason about a goal, decide which tools to use, and execute multi-step tasks — operating on behalf of a user without requiring step-by-step instructions.
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Model Context Protocol (MCP)
Model Context Protocol (MCP) is an open standard introduced by Anthropic in 2024 that lets AI assistants discover and use external tools — like USB-C for AI, providing a universal way to plug models into apps and data sources.
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Multi-Model AI
Multi-model AI is the practice of using different language models for different tasks within a single platform — picking the best model for each job instead of locking yourself into one provider's ecosystem.
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AI Hallucination
An AI hallucination is when a language model generates information that sounds plausible but is factually incorrect, fabricated, or inconsistent with reality — often delivered with high confidence.
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AI Credits
AI credits are a usage-based currency that AI platforms use to meter consumption — different actions (chat, image generation, video, embedding) consume different amounts of credits, giving users flexibility without per-action billing.
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