Antonio Agudo
Founder
Wave Claims
Wave Claims offers a ClaimOS platform that encodes an insurer's exact policy terms and runs AI adjudications validated against this encoded logic in real time. The system creates an immutable audit trail for compliance, automatically routes low‑confidence claims to human reviewers, and supports model‑agnostic AI upgrades.
- Artificial Intelligence
- Insurance Technology
Updated 5 months ago
Funding
Funding rounds are not available yet.
Founders
Patrick Dawson
Co‑Founder
Product
Problem
Insurance carriers rely on manual claims adjudication or generic AI models that lack verification against specific policy terms, leading to claim leakage, high appeal rates, and regulatory risk due to undocumented decision logic.
Solution
Wave Claims’ ClaimOS platform encodes an insurer’s exact policy version, benefit schedules, and exclusions, then runs AI adjudications that are cross‑checked against this encoded logic before entering the claims book. Each decision is validated in real time, producing an immutable audit trail that proves compliance with the carrier’s standards. When the AI’s confidence falls below a configurable threshold, the claim is automatically routed to a human reviewer, ensuring that uncertain cases receive expert oversight. The verification layer is model‑agnostic, allowing insurers to upgrade underlying AI models without altering their policy encoding or compliance framework.
Target Audience
Primary customers are property and casualty insurers and health insurers that need fast, accurate claims processing while maintaining strict policy compliance and auditability.
Features
- Policy‑specific encoding that maps each claim to the active policy version, benefit schedule, and exclusion list at the date of loss
- Real‑time verification layer that validates AI decisions against encoded policy rules before they are recorded
- Immutable audit trail for every adjudicated claim, providing provable compliance and supporting regulatory audits
- Automatic routing of low‑confidence claims to human reviewers based on configurable confidence thresholds
- Model‑agnostic architecture that permits AI model swaps while preserving verification standards and avoiding vendor lock‑in