Zero-Leakage Multi-Tenant RAG Engine
Provable data isolation enforced at the SQL query layer before vector similarity.
The Predatory Economics of Legacy Enrichment
Enterprise clients needed a RAG pipeline where tenant data isolation is provable — not just application-layer filtering, but enforced at the SQL query layer before vector similarity search runs.
Transparent Waterfalling & Zero-Waste Billing
FastAPI + SQLAlchemy 2.0 async + PostgreSQL RLS policies scoped per-request. NVIDIA NIM (nv-embed-v1 + llama-3.1-70b) for embeddings + token streaming over SSE. Isolation enforced at the SQL query layer, provable live.
Core Innovations
Engineered for scale, speed, and safety.
SQL Query-Plan Boundary
PostgreSQL RLS enforces tenant limits prior to index scans, making cross-tenant data visibility mathematically impossible.
NVIDIA NIM Acceleration
Sub-50ms embedding generation with nv-embed-v1 and real-time streaming with llama-3.1-70b.
System Architecture
How the system works under the hood.
Per-Request Scoped Session Context
Every database connection executes a transactional SET LOCAL app.current_tenant prior to executing any vector KNN query.
Technology Stack
Built with precision tooling.
Need a production system built with this level of rigor?
I partner with founders and enterprise teams to architect high-throughput SaaS engines, reliable AI pipelines, and rock-solid web infrastructure.
Book a 30-min Architecture Review