Retrieval-Augmented Generation (RAG)(RAG)
Quick definition
RAG is an AI technique where a language model retrieves relevant information from a knowledge base in real-time before generating a response, making the output more accurate and current.
Detailed explanation
One of the biggest limitations of standard LLMs is that they only have knowledge up to their training date. RAG solves this by giving the model access to an external knowledge source — such as your product documentation, customer data, or company information — at the moment it answers a question. How does it work? The user's question is first converted into a vector (mathematical representation of meaning), after which a vector database retrieves the most relevant documents. Those documents are passed to the LLM along with the question, which then generates an answer based on both its trained knowledge and the specific, current context. For sales and marketing, RAG has enormous applications. Imagine Mario having access not just to general knowledge, but also to your complete product catalog, price lists, case studies, and previous customer conversations.
Synonyms
Examples
A software company implements RAG for their sales agent: the agent has access to all 200+ product features, customer case studies, and competitive comparisons. For a prospect question about integrations, the agent automatically retrieves the most relevant technical documentation.
Match-AI's Mario uses RAG to select the most relevant case study for the specific industry of each prospect — without a human having to do this manually.
When to use this?
RAG is essential when AI systems need to use accurate, current, and company-specific information. Perfect for sales assistants, customer service bots, and internal knowledge systems.
Match-day approach
Match-AI implements RAG systems that make your business knowledge available to Mario. We index your product documentation, case studies, and sales materials in a vector database, so Mario always uses the most relevant and accurate information in his outreach.
Related terms
Large Language Model (LLM)(LLM)
A Large Language Model (LLM) is a neural network trained on enormous amounts of text that understands, generates, and reasons with human language at a human level.
Vector Database
A vector database stores data as mathematical vectors (embeddings) and enables searching based on semantic similarity, rather than exact word matches.
AI Agent
An AI agent is an autonomous software program that independently executes tasks, makes decisions, and communicates with external systems to achieve a specific goal.
Learn more
Wil je weten hoe je retrieval-augmented generation (rag) effectief inzet in jouw organisatie? Neem contact op met Match-day.
Neem Contact Op