RAG applications built
on your data, not guesses.
We design and ship retrieval-augmented generation systems — from document search to AI support agents — that answer from your actual data with citations, not hallucinations.
What you get
Retrieval pipeline design
Chunking, embeddings, and vector store selection tuned to the shape of your data, not a generic template.
Grounded answers
Responses cite source documents, with confidence handling and fallbacks instead of confident wrong answers.
Production integration
Deployed behind your existing app, Slack, support tool, or internal dashboard — not a demo notebook.
Ongoing evaluation
Retrieval quality tracked over time as your data changes, not a one-time launch and walk away.
How we work
Discovery
We understand your business, goals, and challenges.
Strategy
We design the right AI and automation architecture.
Development
We build, test, and optimize your system.
Launch & Scale
We deploy and help you scale with ongoing support.
We use what we sell
Docent
Our own RAG platform, built the way we'd build yours: custom auth, a chunking and embedding pipeline tuned by hand, a relevance threshold calibrated against real questions rather than guessed — with citations on every grounded answer and an honest refusal when nothing relevant exists. Ask it questions, generate an API key, or embed it on a page yourself.
github.com/AdnanQadirKhan/docentPart of 100+ projects delivered for 25+ clients — see the full portfolio.
Common questions
Let's talk about your project.
Book a call or send a request — either way, you'll hear from us with next steps.