Insurer speeds up claim handling with multi-agent application

Manual insurance claim management is slow and ineffective

Claim handlers spend months, sometimes even years, managing a single insurance claim. The process involves manual collection, processing, and validation of multi-source documents, ranging from legal filings and emails to event logs and policy terms.

Data is sourced from fragmented platforms. Documents are updated continuously as investigations proceed. Handlers are forced to spend hundreds of hours manually cross-referencing files to ensure accuracy, leading to slow processes, limited throughput, and poor visibility into claim progress.
 

Multi-agent AI app unifies claim data and cuts time to insight to seconds

We built a multi-agent AI application that provides claim handlers with secure, governed access to claim data in seconds—100% on Databricks.

The system runs multiple agents and pipelines that sort and process claim data and generate insights across the core functions: event summaries, recent updates, legal analysis, etc. It tracks down document updates and makes sure users get accurate, up-to-date information on claim progress. Built-in observability keeps agent and app resource use in check.

As a result, the insurer was able to significantly cut manual workload, allowing handlers to manage more claims with less effort.