Develop a Secure RBI-Compliant RAG System for BanksDevelop a Secure RBI-Compliant RAG System for Banks
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Aman Saraswatiitg
• May 30
Built an RBI-compliant RAG system with enterprise-grade security — because "it answered correctly" isn't enough in regulated industries.
Most RAG systems stop at retrieval. This one has 3 security layers before a single response reaches the user:
→ Layer 1: Adversarial prompt protection Lexical regex filtering catching jailbreak attempts
→ Layer 2: Semantic cosine-similarity detection Catches sophisticated prompt injection that bypasses keyword filters
→ Layer 3: Canary token leak validation Detects if sensitive knowledge base content is being extracted
What else is built in: ✦ FAISS vector search over RBI & fintech policy docs ✦ PII masking — Aadhaar & PAN auto-detected & masked ✦ SHA-256 audit trail on every single query ✦ Explainable AI — every response shows sources + confidence + latency ✦ Human-in-the-loop review for high-risk queries
The result: A RAG system you can actually deploy in a bank — not just a demo.
Stack: Python · FAISS · Sentence-Transformers · ChromaDB · Streamlit · OpenAI API
AI Agent EngineerAI AutomationCybersecurityDockerOpenAIStreamlit
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