I will build a private self hosted rag chatbot over your own documents

Most RAG tools send your documents to an external API. If your data cannot leave your network, that rules them out.

I build retrieval systems that run entirely on your own infrastructure. Local model via Ollama or vLLM, your vector database, no external calls.

I hold an MSc in Data Science from NUST MISIS. Most recently I shipped a production NLP pipeline inside a bank: a local LLM paired with a rule engine, 96-99% agreement with hand-labelled data, every output traceable to a readable rule.

What you get:

Document ingestion and chunking tuned to your file types.

Local model serving, so no data leaves your network.

Vector database setup with source attribution down to page number.

FastAPI endpoints, Dockerised, documented for your engineers.

Handover documentation and a walkthrough call.

On Premium I also deliver an evaluation harness: recall@k, MRR and groundedness measured on your own data, so you can prove the system works and re-run it after I leave.

Message me with what your documents look like and what people need to ask them, and I will tell you exactly how I would build it.