What is RAG?
Retrieval-augmented generation combines a language model with an intelligent document search. Instead of answering from memory, the AI first searches your knowledge base for relevant content – and uses that as the basis for its answer.
The difference from classic chatbots
Classic chatbots answer from their training knowledge. That has two problems: the knowledge is out of date, and the AI hallucinates – it invents answers.
- Searches your real documents semantically
- Delivers answers with source references
- Does not hallucinate – no source, no answer
- Learns from new documents immediately (no retraining)
How KOSMO processes documents
KOSMO splits your documents into “chunks”, converts them into vectors and stores them in a vector database. When a question arrives, it searches semantically for the most relevant chunks – not by keyword, but by meaning.
Semantic search understands that “requesting leave” and “reporting absence” belong to the same topic – even without words in common.
