Automate Claims Processing for Your 20-Person Agency

Most 20-person agencies run on an Agency Management System like Applied Epic, Vertafore, or HawkSoft. These platforms are excellent systems of record, but their built-in automation is fundamentally rule-based. An AMS workflow can trigger an email when a claim status changes, but it cannot read an incoming PDF to decide what that status should be. This leaves your claims team performing high-volume, low-value manual data entry.

Consider this scenario: an FNOL for a commercial auto claim arrives as a PDF in a general inbox. A claims processor must open it, find the policy number, claimant name, and incident details, and then copy each field into the AMS. Next, they make a judgment call on severity and consult a spreadsheet to see which adjuster has the capacity and specialty for the case. This entire process takes 15 minutes per claim and is highly susceptible to copy-paste errors, especially during a post-storm surge when volume triples.

To solve this, some agencies try generic parsing tools. These tools rely on fixed templates, meaning they look for the policy number in the same spot on every document. The first time a carrier updates their PDF layout, the parser breaks, and you are back to manual entry. They lack the contextual understanding to extract the 'date of incident' if it's phrased differently across forms.

The structural problem is that neither your AMS nor simple parsing tools can handle unstructured language. They are designed for structured data and rigid rules. Insurance claims are communicated in variable human language, which requires a system built for semantic interpretation, not just data mapping. You cannot solve a language-based bottleneck with a database workflow tool.

The engagement would begin with a focused discovery and audit. Syntora would analyze 20-30 sample FNOL reports from each of your primary carriers to map out all format variations. We would simultaneously work with you to define the exact data fields required by your AMS, creating a clear data contract that dictates what information needs to be extracted and where it needs to go. This audit ensures the proposed system fits your real-world documents and workflows.

The technical core would be a FastAPI service deployed on AWS Lambda. When an FNOL email arrives, it would trigger the service, which passes the document content to the Claude API. Having built similar document processing pipelines for financial services, we apply the same pattern here. The Claude API reads the unstructured text, extracts key entities like policy numbers and incident dates, scores the claim's severity from 1-5, and returns a structured JSON object. The FastAPI service then connects to your AMS API to create the claim record and assign it based on the severity score.

The final deliverable is a background automation process that requires no change to your team's daily habits. Claims simply appear in your AMS, correctly populated and assigned, within 60 seconds of the FNOL email's arrival. You receive the full Python source code, a technical runbook for maintenance, and complete control over the system running in your own AWS account.