Custom LLM + RAG systems that find, summarize and reason over your private knowledge — contracts, tickets, products, docs, calls. Model-agnostic. Yours to own. Live in 4-6 weeks.
Production RAG: ingestion pipeline, vector DB, retrieval layer, LLM, API.
Embeddable widget OR a JS/Python SDK. Or both. Your call.
Question-answer pairs scored automatically. Run pre-deploy + monthly.
Add/remove docs, see queries, view citations, fix wrong answers.
What questions must it answer? Which docs? Who's allowed to see what? Eval criteria.
Ingestion pipeline. Vector store. Retrieval logic. LLM prompting. Citations.
Run eval suite. Re-rank, re-chunk, re-prompt until you hit your accuracy goal.
Production deploy. Monitoring. Admin panel. Team training. Hand off.
1 data source, 1 use case, embedded widget or SDK. Live in 4 weeks.
Multi-source, multi-tenant, full admin panel, advanced re-ranking.
Multi-modal, on-prem option, SOC 2, dedicated engineer, custom models.
“We needed to search 14,000 pages of clinical guidelines. Two other vendors built RAG systems that hallucinated. iTechNotion’s system cites every answer, refuses to guess, and clinicians actually trust it. We hit 94% accuracy on our eval suite. Finally — RAG that doesn’t lie.”
Not in production. Every answer cites the source chunk. If retrieval doesn't find a confident match, the system says 'I don't have that' rather than guessing. We tune the refusal threshold per use case.
Yes. Default deployment is on Vercel + Pinecone managed. We can deploy entirely in your VPC or on-prem with open-source vector DBs (Weaviate, Qdrant, pgvector) and open-weight LLMs (Llama, Mistral).
We don't train on your data. We don't share it. All embeddings stay in your vector DB. SOC 2 + HIPAA available on Enterprise. We sign DPAs and NDAs by default.
30-min call. Tell us about your data and questions. We'll show you a working demo on a slice of your real corpus.