Posts on what we actually think.
Essays on conformal prediction, social inflation, and where generative AI helps and where it doesn't. Written by the team.
Showing 11 posts · Product
Clear filtersFitting Into an Existing Claims Workflow
Claims adjusters live in their core systems. Forecasting litigation risk requires an architecture that operates entirely in the background and delivers calibrated answers exactly where the work actually happens.
Reserve Delta, Escalation Probability, Comparables: The Feature Set
A single point prediction is useless in litigation. Claims forecasting requires calibrated ranges and traceable drivers to survive the scrutiny of a reserving committee.
A Forecast for Every Open Claim: The API
A forecast isn't useful if it lives in a silo. We built the Canotera API to inject calibrated settlement ranges and reserve deltas directly into the systems where adjusters already work.
Security and Data Handling for Sensitive Claim Records
Handing thousands of pages of raw medical and legal records to a third-party AI pipeline is a CISO's nightmare. Building a forecasting platform for insurance claims requires treating data as a liability and engineering for pessimism.
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