The problem
Claims and submissions arrive as PDFs, photos, and email threads. Adjusters and underwriters spend their days re-keying documents and chasing missing information, while turnaround stretches to days or weeks — and the industry has already proven this class of work automates.
The system
An intake pipeline that extracts and validates document data with per-field confidence, checks policy conditions and eligibility rules deterministically, routes clean cases straight through to decision or quote, and assembles an evidence-linked case file for everything that needs a human. Fraud and severity signals ride along; the human always owns the edge cases.
How it's built
- Layout-aware document extraction with field-level confidence and validation rules
- Deterministic policy/eligibility engine; models only where judgment is genuinely required
- Straight-through path with audit trail; exception queue with pre-built case files
- Eval set from historical claims — automation rate and error rate reported, not guessed
Delivery
A Sprint on a few hundred historical claims measures achievable straight-through rates honestly; Build wires the pipeline into your core systems.
What to expect
- A measured straight-through rate on the clean majority of cases
- Turnaround on automated cases measured in minutes
- Adjusters working exceptions with the reading already done
Documented results in the wild
Independent, published deployments of this class of system — cited as market evidence that it works at scale. These are not our clients.
- Lemonade AI claims agent settled a real theft claim in 2 seconds; roughly 40% of claims need no human at all. Reinsurance News, 2023 ↗
- Zurich Insurance AI paperwork review cut injury-claim processing from one hour to five seconds, saving 40,000 work hours. Insurance Journal / Reuters, 2017 ↗
- Hiscox GenAI underwriting intake cut London-market quote turnaround from up to three days to three minutes, live in production since 2024. Hiscox Group, 2023–24 ↗