Enterprise Operations
Internal AI document intelligence & workflow agents
Insurance operations60,000 documents / month4 systems of record
The problem
Sixty thousand documents a month, claims, endorsements, broker correspondence, were keyed by hand into four systems of record. Fourteen-day backlogs were normal; quality audits caught errors weeks after they had propagated downstream. Headcount could not scale with intake, and the best analysts spent their days retyping PDFs.
What shipped
- LLM extraction pipeline with confidence-gated outputs
- Workflow agents filing into all four systems of record
- Exception review console for the cases that need a human
- Continuous evaluation against human corrections
Problem-to-production blueprint
1DiagnosisDocument taxonomy and exception analysis, which 20% of document types caused 80% of rework.
2Architecture & PoCConfidence-gated extraction proven on 10,000 historical documents against known-good values.
3Production engineeringFiling agents with per-system rollback, exception console, and full processing audit log.
4StewardshipHuman corrections feed continuous evals; scope expanded to two more document classes per quarter.
Outcomes
4 hrsProcessing, was 14 days
78%Straight-through, from 12%
1,200Analyst hrs/mo reclaimed
Back-office throughput
Document intelligence that clears the backlog, not adds to it.
Confidence-gated extraction, agents filing into your systems of record, humans on the exceptions.