ClaimArbiter

ClaimArbiter shows how an insurance claim can move from filing to a signed decision in minutes, with AI agents doing the legwork and a human keeping the final say. The problem: insurers rarely employ the specialists they rely on. So a claim usually waits in a queue, gets emailed to an outside assessor, and comes back days later with no shared record of who decided what. The solution: ClaimArbiter compresses that cycle into one live workspace. Intake reads the claim and classifies its domain. An Evidence Analyst inspects the photos and documents. A Case Coordinator recruits the matching property, medical, or legal specialist across a company boundary, with consent. The specialist returns an approve or deny recommendation, and a human reviewer signs it back into the same room. Every message, handoff, and decision is stored in Band as a tamper-evident audit trail you can replay and verify. It includes analysis of text, images, and pdf documents. The target audience is insurers and claims teams who want faster, auditable decisions, plus anyone building multi-agent systems that must cross company and framework boundaries. What makes it unique: the specialist routing is real, not scripted. The same system sends a water-damage claim to a property assessor, an injury claim to a medical reviewer, and a legal-expense claim to a legal reviewer. The agents are built with three different AI frameworks and run on different AI models, yet they collaborate in one shared room with a human in the loop.