Private AI Architecture
Private RAG Systems for Secure Enterprise Knowledge
Turn internal documents and operational data into a permission-aware answer layer without copying sensitive knowledge into a public AI service.
Schedule a technical consultationThe enterprise problem
Designed around the risk you need to remove.
Enterprise search fails when people cannot find the right version of a policy, contract, runbook, or technical record. A private retrieval-augmented generation system connects those sources to grounded answers while preserving document permissions, provenance, and the ability to inspect how an answer was produced.
Technical methodology
A system boundary you can inspect.
The architecture is decomposed into explicit layers so data movement, authorization, operational ownership, and failure behavior remain visible.
- 01
Ingest and classify
Connectors extract content, metadata, ownership, retention, and source-system permissions.
- 02
Hybrid index
Lexical search, vector retrieval, metadata filters, and reranking work together for high-recall discovery.
- 03
Grounded generation
A private model receives only authorized context and returns citations to the source material.
- 04
Feedback loop
Evaluation sets, user feedback, retrieval traces, and drift monitoring improve the system over time.
Security & compliance
Controls belong in the design.
Security is not a deployment afterthought. It is expressed through identity, isolation, data handling, auditability, and the ability to recover safely.
- Document-level and row-level authorization inherited from source systems
- Private embeddings and indexes stored in the approved environment
- Source citations and retrieval traces for every answer
- Retention, deletion, and re-indexing controls
- PII redaction and prompt-injection defenses at ingestion and query time
What this enables
Built for ownership, trust, and the next stage of growth.
- Faster access to trusted internal knowledge
- Lower hallucination risk through citations and evaluation
- A measurable search experience for teams, not just a chat interface