Implement Voice AI for Your Inbound Insurance Calls

Most regional insurance firms rely on a customer service representative and a standard VoIP phone system to handle inbound calls. The CSR must manually identify the caller's intent: Is this a new claim? A question about a policy? A renewal request? This process is slow and creates a bottleneck, especially during peak events like a storm.

Consider a customer calling about a minor fender-bender. They sound distressed, so the CSR routes the call to a senior claims adjuster. The adjuster spends ten minutes gathering First Notice of Loss (FNOL) details for a low-severity claim, while a more complex commercial liability call waits in the queue. The CSR made a judgment call based on emotion, not on the factual details of the incident. This misallocation of resources happens dozens of times a day.

The structural problem is that phone systems are designed to route calls, not understand them. Off-the-shelf Interactive Voice Response (IVR) systems try to solve this with rigid phone trees ("Press 1 for claims, Press 2 for billing"). These systems fail when a caller's need is nuanced, like a policyholder asking a question that will lead to filing a claim. The rigid logic cannot adapt, forcing the caller to 'zero out' to an operator, defeating the purpose of the automation.

The first step would be to audit your existing call flows and triage logic. Syntora would work with one of your experienced agents to map the primary call types, the key information needed for each, and the correct routing destination. We would analyze a sample of anonymized call transcripts to identify the specific language patterns that distinguish a high-severity claim from a routine policy question.

The technical approach would use an AWS Lambda function to orchestrate the process. When a call comes in, the audio stream is converted to text. That transcript is sent to the Claude API with a carefully engineered prompt to extract intent, entities (like policy number), and a severity score. This structured data is then stored in a Supabase database and exposed via a secure FastAPI endpoint for your AMS to consume. This architecture processes a 5-minute call in under 3 seconds for a hosting cost of less than $50/month for moderate volume.

The delivered system would integrate directly into your existing workflow. For an FNOL call, the system could create a new task in Applied Epic or HawkSoft with the transcript, a summary, and the caller's details pre-filled. For a policy question, it could route the call to the correct agent's extension along with a screen pop showing the customer's account. The goal is to assist your team, not replace their judgment.