Knowledge Base and RAG

A reliable agent needs reliable knowledge. We organize documents, web pages, FAQs, business rules and product information into a searchable and maintainable knowledge base.

What we design

Content structure, chunking, retrieval quality, citations, update flow and permission boundaries are all part of the implementation.

Use cases

Sales support, internal training, service explanation, policy lookup and product guidance all benefit from a clear RAG layer.

FAQ

How is the knowledge base kept up to date?
We design an update pipeline. When source documents change, the knowledge base can refresh automatically so the agent always responds with current information.

Do you support multiple models with RAG?
Yes. RAG can work with OpenAI, Claude, DeepSeek, Qwen, Gemini, local models or private models, choosing the right model per query type.