What it sells
AI agents for insurance claims operations
Business model breakdown
Buyer: who owns the budget?
Claims leadership and IT at insurance carriers and TPAs (case study quote from the VP of IT at Athens Administrators).
Trigger: what makes them buy now?
High inbound call volume overwhelms adjusters and delays claims work (challenge stated in the Athens Administrators case study).
Workflow: what inputs become what output?
AI agents take FNOL intake by phone, email or file upload, answer claim-status calls, auto-dial employers, providers and injured workers, parse claim files into chronologies, and give adjusters a copilot that cites sources and suggests next actions, all written back to the claims system.
Economics: what it saves and how it charges
Custom pricing driven by claim volume, integration complexity and features; case study reports 64% of inbound calls resolved automatically.
Distribution: how it reaches customers
Demo-led enterprise sale with forward-deployed engineers integrating into claims systems, starting with a Proof of Value on production claims.
Funding history and coverage
| Round date | Stage | Amount | Investors | Source |
|---|---|---|---|---|
| — | Y Combinator Spring 2025 | — | Y Combinator | ycombinator.com |
Profiles summarize public reporting and company websites. Business-model notes are MaxBC's reading of that material, not confirmed facts; unknowns are left blank rather than guessed. Updated 2026-10-12.