The problem
Teams lose time searching long documents and risk receiving confident answers that are not connected to approved information.
RAG
RAG Knowledge Assistant
A grounded knowledge assistant that retrieves relevant business information before generating a clear response.
System view
Product overview
A retrieval-augmented generation system built to answer questions from an approved knowledge base. The workflow focuses on useful chunking, retrieval quality, metadata filters, and transparent source grounding.
The solution
The assistant first retrieves the most relevant source material and then uses that context to compose a focused answer.
Core functions
What the product is designed to do.
- Document cleaning and structured chunking
- Hybrid semantic and keyword retrieval
- Metadata-aware context selection
- Grounded answer generation
Technology
A practical, production-minded stack.
- Python
- LangChain
- Vector Search
- FastAPI