AI for insurance — where speed of quoting and claims, and auditability, both matter.
A submission has to get quoted before the broker moves on, and a claim has to get triaged before the adjuster's queue backs up — and every one of those decisions can end up in front of a regulator, a reinsurer, or a plaintiff's attorney. I build AI for that reality: fast, grounded, and fully auditable, for carriers, brokers, MGAs, and insurtech.
Experienced working within
Insurance runs on a contradiction most AI vendors gloss over: the business rewards speed — quote fast, bind fast, pay claims fast — while the risk sits in the opposite direction. Every underwriting call and every claims decision is a data point a regulator, a reinsurer, or a courtroom can revisit years later.
I build AI that holds both ends at once. Grounded retrieval so answers come from your policies, forms, and loss history — not a model's guess. Append-only audit trails so every recommendation can be traced back to what it saw and why it flagged it. Fast where the business demands it, provable where the exposure does.
Where AI moves the number
The highest-impact work in an insurance organization is high-volume, document-heavy, and expensive in underwriter and adjuster hours — exactly where a well-built agent earns its keep.
- Underwriting support — risk signal aggregation, appetite matching, and submission triage that gets the right file in front of the right underwriter, faster.
- Claims automation — intake, triage, routing, and fraud signal detection that clears the straightforward claims and surfaces the ones that need a human.
- Submission & document intake — extracting structured data from ACORD forms, loss runs, and broker submissions so nothing sits in an inbox waiting to be typed up.
In this industry, an underwriting or claims decision you can't explain is a liability, not a shortcut. I build systems that show exactly what data drove the call — and who's accountable for it.
Four places AI pays for itself in the book of business.
From briefing to production, with the controls built in.
Find the highest-impact use case
Underwriting triage, claims intake, or submission processing — we pick the one that moves a real number and agree on the KPI up front.
Design for speed and audit together
Grounded retrieval, the audit layer, and regulatory-aware deployment are designed as one — fixed scope and price, no surprises.
Deploy into your environment
We build in sprints, deploy inside your controls — on-prem where the policyholder data demands it — and harden until it holds under real volume.
Prove the value and the trail
We track the system against its KPI and confirm every decision is logged and provable — then tune until the value crosses the cost.
Let's talk about where AI moves a number in your book.
Underwriting support, claims automation, submission intake — if it's high-volume and it has to be provable, that's my kind of problem. I'll tell you what it's worth before we build it.
