Service · Nocta AI Studio
RAG Knowledge System
We build a retrieval system over your real documents and data, so AI answers ground in your facts — not the open internet.
/ The problem
What this service solves.
Teams have years of documents, tickets, specs and notes. Most of it is unreachable in the moment of need. Generic AI does not know any of it.
/ What's included
The work itself.
- Source inventory (docs, drives, wikis, tickets)
- Ingestion and chunking pipeline
- Embedding and retrieval design
- Quality evaluation on real questions
- Search or assistant interface
/ Outcome
What you walk away with.
A working knowledge system where the right document, paragraph or answer is one question away.
/ How it fits
Where this sits in the studio.
Sits underneath LLM Integration and Custom AI Agent builds when knowledge is the bottleneck.
/ Next step