Automate Claims Triage to Get Your Adjusters on the Right Cases Faster

Most small agencies rely on their Agency Management System for workflows. Platforms like Applied Epic, Vertafore, or HawkSoft have triggers and automation rules, but they depend entirely on structured data. They cannot read an unstructured email or a scanned PDF containing a First Notice of Loss (FNOL) report. This inability to process raw information creates a critical manual bottleneck right at the start of the claims process.

Consider a 15-person agency that receives a new commercial auto claim. The FNOL arrives as a PDF attachment in an email. A customer service representative must open the email, download the PDF, read the incident description, and manually identify the policy number, claimant, and incident date. They then decide the claim's severity. Is it a minor cracked windshield or a multi-vehicle collision with injuries? This judgment call determines if it goes to a junior or senior adjuster. The CSR then logs into the AMS, creates a new claim file, and re-types all the information from the PDF. This takes 20-30 minutes per claim.

This manual process is not just slow, it is prone to error. If the CSR misjudges the severity, a complex claim can be assigned to a junior adjuster, delaying resolution and affecting customer satisfaction. If they mistype a policy number, the claim might be linked to the wrong account. The structural problem is that an AMS is a database for storing information, not a tool for understanding it. The system's architecture requires humans to act as the bridge between the unstructured world of client communications and the structured world of the database.

The first step would be a data audit. Syntora would review 50-100 anonymized examples of your past FNOL reports, including emails, PDFs, and any attached images. This audit maps every data format and identifies the key fields required for accurate triage, such as claimant name, policy number, incident description, and loss type. We would work with your team to codify your existing adjuster routing logic into a clear set of rules.

We would build the core system as a Python service running on AWS Lambda, triggered by new emails to your claims inbox. The Claude API would parse the email body and attachments, extracting the necessary data into a structured format defined by Pydantic schemas. A separate function would apply your business logic to score the claim's severity and determine the correct adjuster assignment. The system would then connect to your AMS API, for example the Vertafore API, to create a new claim record and assign it to the right person. The entire workflow, from email receipt to adjuster notification, would complete in under 60 seconds.

We have built similar document processing pipelines for financial services firms, using the Claude API to extract data from loan applications. The pattern of parsing unstructured documents to trigger a downstream workflow applies directly to insurance claims. The delivered system runs in the background. Your team uses the same AMS they use today, but new claims would appear automatically, already triaged and populated with the correct data. You receive the full source code, a runbook for monitoring, and complete control over the system, which runs in your own AWS account for under $50 per month.