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All case studies

Financial services · AI · 2025

A compliance copilot that reads SEC filings in seconds

A mid-market asset manager was burning analyst hours skimming filings for material risk language. We built an AI system that reads 10-Ks, 10-Qs and earnings transcripts, extracts material claims, and routes them to a human reviewer with citations.

Industry
Asset management
Duration
11 weeks
Team
4 engineers

Headline result

−82%

review time

Review time
−82%
Cost per filing
$0.18
Eval pass-rate
94.6%
Filings indexed
60k

The challenge

What needed to change.

Compliance and credit teams were spending 30+ hours a week reading filings — slow, expensive, and impossible to scale as the firm's portfolio grew. Off-the-shelf tools missed nuance and gave their analysts no way to verify the model's output.

Leadership wanted to ship something safe enough to deploy to a regulated team in under a quarter, with a clear path from prototype to production.

Our approach

How we built it.

We designed a multi-agent system: a planner decomposes the analyst's question, a retriever fetches relevant filings, a critic evaluates extractions against ground truth, and a writer composes the final answer with citations.

Every output is grounded in cited source text. We built an eval harness over 1,200 hand-labelled extractions, and ran every prompt change against it before promoting to production.

Highlights

  • Multi-agent architecture — planner, retriever, critic, writer
  • Hybrid retrieval over 8 years of SEC filings
  • Eval harness with 1,200 hand-labelled extractions
  • Cost capped at $0.18 per filing reviewed
  • Audit trail for every decision the system makes
ClaudeGPTPostgres + pgvectorModalTypeScript

Outcome

What changed.

Eleven weeks from kickoff to production rollout to the compliance team. Review time fell 82%, cost per filing was bounded, and the firm's analysts now spend their hours on the questions only humans can answer.

Review time
−82%
Cost per filing
$0.18
Eval pass-rate
94.6%
Filings indexed
60k
DS OPS shipped what our internal team couldn't ship in two years. They re-architected our AI pipeline in seven weeks. Production cost dropped 60%.
V

VP, Engineering

Series-B financial services

Booking the next quarter

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