AI for insurance carriers, grounded in your own guidelines and auditable end to end.
Bluegrass builds production AI systems for insurance carriers, from underwriting assistants grounded in your guidelines to claims summarization. Each keeps an audit trail that a regulator or your model risk team can follow, runs in your own cloud and belongs to you.
Carriers rarely lack AI pilots, but few of them reach production. A demo on clean documents says little about accuracy on a year of real submissions or about the day a model provider changes something.
Where a carrier's time goes
Underwriting
Underwriters spend much of their time gathering and reading information before they can apply judgment: applications, loss runs, inspection reports and the guidelines themselves.
Submission triage
Submissions from brokers and MGAs need classifying, clearing and prioritizing before an underwriter sees them.
Issuance and checking
Issued policies and endorsements have to match what was bound, and an error at issuance becomes a dispute at claim time.
Claims
Adjusters read long files of notes, reports and correspondence to understand a claim before they can act on it.
What we build for insurance carriers
Underwriting assistants
Assistants that gather the file, apply your guidelines and draft the referral or the quote rationale, with every statement linked to its source.
Claims summarization
Claim files summarized as they grow, so an adjuster or supervisor can see the current position without rereading every note, with a defensible audit trail.
These are examples of what we can build for insurance carriers. Pick one up as-is, have it tailored to you or suggest something entirely new.
Talk to an engineerWhere to start
For a carrier we recommend starting with triage or policy checking, where accuracy can be measured cleanly against decisions your people already make. Assistants that support underwriting and claims judgment come after.
Every system ships with the evaluation harness, monitoring and documentation model risk and compliance teams ask for, which usually decides whether a pilot reaches production.
Questions and answers for insurance carriers
- How do you handle model risk management?
- Each system comes with what a model risk review needs: a documented evaluation set, accuracy measured before launch and monitored after, version control and a record of every output.
- We have our own data science team. Why bring you in?
- The engagements that work best pair us with that team. We bring experience taking these systems into production on insurance documents, and your team takes the system over, fully documented, once it is live.
- Can it run inside our own environment?
- The systems are deployed into your own cloud accounts and read your data in place, and the choice of model is made with your security team.
- Will it work with our core systems?
- The systems connect to the policy administration, claims and document platforms you run, and the evaluation confirms how before anything is built.
A senior team that has done this before
We are a small, entirely senior team with fifty years of combined AI engineering, multiple granted patents and Y Combinator founders, from Yale, MIT, McKinsey, Goldman Sachs, Microsoft and Vista Equity Partners. The people who scope your work are the people who write the code.
Selected work
We built the AI transformation roadmap for a top-50 P&C brokerage, and it is saving the firm millions of dollars in vendor fees it did not need to pay.
Clients include some of the largest banks, RIAs, fintechs and AI labs, as well as a top-3 P&C carrier, a top-10 P&C brokerage, a top-5 trucking brokerage, a leading specialty MGA and a leading trucking MGA.
We run only 3 to 5 engagements at a time, so that every client works directly with the senior team.
About the team- Dozens
- of insurance companies, RIAs, banks and fintechs we have worked with
- 50 yrs
- combined AI engineering experience
- 10+ Patents
- granted to members of the team
- 100%
- of the IP we build is assigned to you
Tell us which workflow costs your team the most time.
A 30-minute call with an engineer usually shows whether something is worth building. Within a week you will have a free written point of view on the two or three opportunities we think are real and what each is worth.