Enterprise AI Knowledge Engine & Automated Compliance RAG
Indexing 15M+ internal technical and legal contracts with sub-second semantic retrieval and strict RBAC.
Key Business & Engineering Outcomes
Contract review cycle dropped from 4.5 hours to 35 minutes
Verified precision on complex multi-jurisdiction contract clauses
Historical case law and regulatory filings indexed securely
Air-gapped private model deployment preserving attorney-client privilege
The Business & Technical Challenge
Attorneys and compliance officers spent an average of 4.5 hours per contract performing cross-jurisdictional compliance reviews and historical precedent matching.
The Entecra Architectural Solution
We engineered a private hybrid-search AI architecture combining pgvector, Milvus vector databases, fine-tuned LLM embeddings, and strict enterprise permission filtering.
Architecture Blueprint & Implementation Phases
Automated Document OCR & Chunking
Built a resilient parsing pipeline converting complex multi-column legal PDFs and scans into semantically segmented tokens.
Context-Aware Vector Indexing
Generated domain-specific embeddings stored in an encrypted pgvector cluster with hybrid BM25 re-ranking.
Enterprise Guardrails & Strict Citations
Constructed an evaluation harness ensuring all answers contain verifiable pinpoint page citations with zero data leakage.
“Entecra’s AI solution didn’t just speed up our workflow—it fundamentally elevated the analytical depth and accuracy of our legal deliverables.”
Architecture & Tech Stack
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