Every component of the AI pipeline runs on your infrastructure. Your documents never leave your network — not even as query fragments.
All four pillars of the RAG pipeline operate inside your infrastructure boundary.
Local embedding models convert documents into vectors without any external calls.
All indexed vectors stored on your servers. Search and retrieval happen locally.
Open-source LLMs (e.g. Llama, Mistral) run entirely on your GPU hardware.
Query processing, re-ranking, and answer generation — all within your network.
No document content, embeddings, or queries ever leave your network perimeter.
Runs in fully disconnected environments — no internet connection required at any point.
Simplifies GDPR, HIPAA, and industry-specific compliance by eliminating third-party data transfers.
Fixed hardware and licensing costs. No per-token fees, no usage surprises.
You own the models, the data, and the infrastructure. Update, audit, or customize at will.
Every query, retrieval, and response is logged locally for full traceability.
Client privilege and case documents require absolute confidentiality. No cloud exposure.
Clinical trial data, patents, and research documents under strict regulatory oversight.
Financial records, compliance documents, and customer data with zero tolerance for leaks.
Classified and sensitive documents in air-gapped environments with security clearance requirements.
Policy documents, claims data, and customer records requiring data residency guarantees.
We evaluate your infrastructure, document volume, and security requirements to design the optimal deployment.
KADARAG is installed on your servers — Docker, Kubernetes, or bare metal. Full setup in days, not months.
Your team starts querying documents with AI. We provide training and ongoing support.
See the fully offline RAG pipeline running on your own infrastructure.
Schedule a Demo