Automate Inbound Call Triage for Your Insurance Agency
An AI agent transcribes inbound calls and extracts key details like policy number and incident type. It then scores claim severity and routes a summary to the correct adjuster with next steps.
Syntora helps independent insurance agencies understand how an AI agent can handle inbound customer service calls. We outline a technical approach for building systems that transcribe calls, extract key details, and route summaries to adjusters. Our focus is on designing and delivering custom solutions, informed by our experience with similar AI architectures in adjacent domains.
A system designed for this purpose would integrate with your agency management system, such as Applied Epic, Vertafore, or HawkSoft. The complexity of the engagement depends on the number of call types to handle, from new claims (FNOL) to policy questions, and the structure of your existing client data.
Syntora designs and builds such systems based on your specific requirements. We've developed document processing pipelines using Claude API for sensitive financial documents, and the same architectural patterns apply to insurance call transcripts. A typical engagement to develop and deploy an AI call handling system of this complexity usually spans 10-16 weeks. This includes initial discovery, architecture design, development, and user acceptance testing. To begin, clients would provide access to relevant APIs for their phone system and AMS, along with sample call recordings and documentation on their existing workflows.
What Problem Does This Solve?
Most agencies use a standard phone system's auto-attendant, like RingCentral or Dialpad. These systems can route calls based on keypad input but cannot understand the content of a voicemail. This forces an admin to manually listen, transcribe key details, look up the client in the AMS, and forward a summary to the right adjuster, a process that takes 20-30 minutes per claim.
A typical scenario involves a client leaving a frantic voicemail about a car accident. The message sits in a general inbox until an admin is free. By the time the adjuster receives the summary an hour later, the client is already frustrated. This manual triage creates a bottleneck, especially after a storm when call volume can increase 5x, leading to significant delays and poor customer experience.
Off-the-shelf voice AI platforms are built for large carriers with standardized data, not for independent brokers. They are expensive, inflexible, and rarely offer pre-built integrations for agency management systems like HawkSoft. You are left with a system that cannot access the core information it needs to make an intelligent routing decision.
How Would Syntora Approach This?
Syntora's approach to building an AI call handling system for independent insurance agencies begins with a discovery phase to understand your specific call types, routing rules, and data structures. Following discovery, we would design an architecture tailored to your needs.
The system would connect to your existing phone system's API to receive call recordings or transcripts automatically. For transcription, the Deepgram API offers high accuracy for phone audio, making it a strong candidate for this component. Concurrently, the system would pull policy and adjuster assignment data from your AMS, like Applied Epic or Vertafore, to maintain a current map of your client base.
The core logic would be built using the Claude API. Syntora would engineer prompts to ingest the raw transcript, extracting structured data such as claimant name, policy number, incident type, and contact information. A subsequent prompt would generate a concise summary, recommend next steps, and assign a severity score on a 1-10 scale.
A FastAPI application, deployed on AWS Lambda, would serve as the central coordinator. When a call concludes, your phone system would send a webhook to this API. The API would then process the transcript, retrieve the assigned adjuster from a Supabase database that syncs with your AMS, and push a notification to the adjuster via email and Slack. Every AI decision and its confidence score would be logged for audit purposes.
For any claim scoring above a 7, the system would automatically flag it for human review, creating a task for a senior adjuster to verify the AI's summary before further action. Syntora configures structured logging using `structlog` and sets up CloudWatch alarms to monitor for issues such as an API error rate exceeding 1% or latency surpassing 90 seconds. The expected monthly hosting costs on AWS for a system of this design are typically under $50. The deliverables for such an engagement include a deployed, custom-built AI call handling system, complete source code, and comprehensive documentation.
What Are the Key Benefits?
First Response in 12 Minutes, Not 4 Hours
Our claims triage system gets vital information to your adjusters instantly, cutting down client wait times and demonstrating immediate responsiveness.
Eliminate Manual Call Triage Costs
Stop paying staff to listen to voicemails and type summaries. This system pays for itself by freeing up hundreds of administrative hours per year.
You Own the Code and AI Prompts
You receive the full Python source code in your own GitHub repository. There is no vendor lock-in; your asset is yours to modify or extend.
Proactive Monitoring via CloudWatch Alerts
We build monitoring directly into the system. You get alerted if performance degrades, ensuring issues are caught before they impact operations.
Connects Natively to Your AMS
Direct API and webhook integrations with Applied Epic, Vertafore, and HawkSoft mean the system works with your existing tools. No new software for your team to learn.
What Does the Process Look Like?
System Discovery (Week 1)
You provide read-only API access to your phone system and AMS. We map your current call flows and define routing rules. Deliverable: A detailed process map and technical specification.
Core AI Development (Weeks 2-3)
We build the transcription-to-summary pipeline using the Claude API and FastAPI. You review sample outputs for key call types. Deliverable: A working API endpoint with documentation.
Integration and Testing (Week 4)
We connect the API to your live systems in a staging environment. We process 50 historical call recordings to validate accuracy. Deliverable: A private staging link for your team to test.
Deployment and Handoff (Weeks 5-8)
We deploy the system to production and monitor it for four weeks to handle edge cases. Deliverable: Full source code, a runbook for maintenance, and a 30-day post-launch support plan.
Frequently Asked Questions
- What does a system like this cost and how long does it take?
- A standard FNOL triage system for a single agency takes 4-6 weeks to build and deploy. The primary cost factors are the number of distinct call types to handle, the complexity of your routing logic, and the quality of your AMS API. We provide a fixed-price proposal after a discovery call.
- What happens if the AI misunderstands a call or the system goes down?
- If the AI's confidence score on a summary is below our threshold, the call is automatically flagged for manual human review. If the entire system fails, a fallback rule routes all incoming call notifications to a single emergency inbox and triggers an alert. No customer message is ever lost.
- How is this different from a virtual receptionist service like Smith.ai?
- Virtual receptionists are humans following scripts for simple tasks like appointment booking. They cannot perform deep, integrated work like looking up policy details in Vertafore or assessing claim severity. Syntora builds an automated system that becomes part of your core insurance workflow, not just an answering service.
- How accurate is the transcription and summary?
- We use transcription models that achieve over 95% word accuracy on phone call audio. The Claude API's summarization is extremely reliable for extracting facts. For subjective tasks like severity scoring, we calibrate the model against your own team's historical assessments and include a human review gate for all high-stakes claims.
- Can it handle calls that aren't about new claims?
- Yes. The first step in the AI pipeline is to classify call intent. The system can be trained to distinguish between a new claim, a status update request on an existing claim, or a billing inquiry. Each call type can then be routed to a different person or workflow automatically.
- How is sensitive customer data handled?
- All processing happens in a secure, private AWS environment. We do not store call recordings or full transcripts after the summary has been generated and routed. Any personally identifiable information is redacted from system logs. We can also deploy the entire system within your own cloud account if required for compliance.
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