Banking: Risk, Compliance, and Legal Departments
Banking GenAI case study for on-prem regulatory query and legal research acceleration.
About Customer
The customer is a banking enterprise requiring secure, high-performance access to large regulatory corpora for risk, compliance, and legal teams.
Strict requirements included on-prem deployment, source traceability, and support for high concurrent usage.
Problem Statement
Teams needed rapid answers from complex regulatory documents, but existing workflows were slow and difficult to audit. Security constraints prevented cloud-based alternatives for sensitive datasets.
A recurring customer story came from legal and compliance analysts preparing internal responses under strict deadlines. They had to search Basel guidance, internal policy exceptions, and prior interpretations manually, then cross-check each finding for evidentiary traceability. The response quality depended heavily on who handled the case, and documenting source justification consumed almost as much time as the research itself.
- Need for on-prem deployment and high data control over sensitive regulatory corpora.
- Demand for accurate answers with clickable source links and audit-ready traceability.
- Scalability requirement for 1000+ concurrent users across risk, compliance, and legal teams.
Solution Architecture
Zettabolt deployed a secure, fully on-premise LLM + RAG (Retrieval-Augmented Generation) system built with ZettaLens. Custom document parsing combined with a fine-grained chunking strategy - splitting regulatory text into small, precise excerpts the AI can retrieve accurately - guarantees the required 80% query accuracy with clickable source backlinks on every answer. Zettabolt's hardware-accelerated retrieval layer keeps it responsive even at 1000+ concurrent users with sub-second response - entirely inside the bank's network with no data ever leaving - and accelerates research time by up to 67%. Here is how we integrated the pipeline:
Implementation Highlights
- Deployed a secure on-prem LLM + RAG stack to satisfy data-residency and internal security controls.
- Implemented granular chunking, reranking, and citation backlinking to improve answer quality and audit defensibility.
- Added role-based policy filters so responses respect user entitlement boundaries by function and domain.
- Optimized inference and retrieval infrastructure for high-concurrency demand with consistent response latency.
Implementation context: The deployment balanced strict security requirements with high-performance retrieval goals, enabling legal and compliance teams to research faster while preserving traceable evidence chains.
Business Impact
Risk, compliance, and legal teams shifted from manual interpretation cycles to a traceable research workflow where each response includes defensible evidence, improving both speed and confidence.
