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Finance

Document review time cut by 82% with LLM-powered intelligence

Built a production RAG pipeline that automated compliance document analysis for a mid-market financial services firm.

82%
Review time reduction
94%
Documents processed autonomously
14 → 2.5days
Average cycle time
more reviews
Analyst capacity freed

The challenge

A mid-market financial services firm was processing over 3,000 regulatory and compliance documents per quarter — manually. Analysts spent 60% of their time extracting key clauses, flagging deviations, and summarising findings. Review cycles averaged 14 days per document package, creating bottlenecks ahead of quarterly reporting and audit deadlines.

Our approach

We ran a 3-week discovery to map document types, analyst workflows, and accuracy requirements. Rather than fine-tuning a model from scratch, we designed a retrieval-augmented generation pipeline grounded in the firm's own policy library and historical review decisions. A human-in-the-loop validation layer was built from the start to handle edge cases and maintain regulatory defensibility.

The solution

The system extracts, classifies, and summarises key clauses from incoming documents, cross-references them against internal policy frameworks, and surfaces deviations for analyst review. Processing time dropped from 14 days to 2.5 days. Analysts now spend their time on judgment calls, not extraction. The system handles 94% of documents without escalation; the remaining 6% are flagged with full context for senior review.

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