This is like giving your claims department a tireless digital assistant that reads claim forms, photos, and documents, checks them against policy rules and past cases, and then drafts decisions and payouts for humans to approve—rather than people doing everything manually.
Traditional claims processing is slow, manual, and error-prone, leading to high operating costs, long payout times, leakage from inconsistent decisions, and poor customer experience. AI automates intake, triage, fraud checks, and decision support to speed up payouts while reducing costs and mistakes.
Tight integration with existing claims workflows and core systems, plus proprietary historical claims and fraud data that continuously improves models and is difficult for new entrants to replicate.
Hybrid
Vector Search
Medium (Integration logic)
Context window cost and latency when processing large, unstructured claim files at peak volumes, plus integration and data-governance constraints with legacy core systems.
Early Majority
Positioned as an AI-first claims layer that automates intake, triage, fraud checks, and decision support on top of existing core systems, emphasizing configurable workflows and use of both unstructured (documents, images) and structured policy data rather than just rules engines or point fraud tools.