Replace Manual Claims Triage with AI Automation
Insurance agencies replace manual claims triage with AI to cut response times and improve accuracy. AI automation parses incoming claims, scores severity, and routes them to the correct adjuster instantly.
The system works by connecting your email or First Notice of Loss (FNOL) intake forms to an AI model. This model reads claim text, categorizes the event, and extracts key details. It is designed for independent agencies managing 100 to 500 new claims per month.
We built a triage system for a 6-adjuster agency that handled complex commercial claims. They cut their average first-response time from 4 hours to 12 minutes. The project was live in production in four weeks.
What Problem Does This Solve?
Agencies often try to automate intake with their Agency Management System (AMS) like Applied Epic or Vertafore. These systems can create tasks from emails, but their rules engines are brittle. A rule that routes based on keywords like "auto accident" breaks when a client writes "car crash" or "hit my vehicle," sending high-priority claims to a general queue.
Consider an FNOL report arriving via email at 5 PM on a Friday with the subject "Urgent Issue". The AMS rule engine sees "Urgent" and flags it, but it cannot read the attached PDF to understand it is a major commercial property water damage claim. The on-call adjuster for auto claims gets the notification and ignores it. The claim sits until Monday morning, delaying response by over 60 hours.
This keyword-based approach fails because it lacks context. It cannot differentiate between a minor fender-bender and a multi-vehicle pileup if both contain the word "accident". It cannot parse unstructured data from PDFs or email bodies. This forces adjusters to spend hours every day manually reading, categorizing, and assigning every new claim, creating a permanent bottleneck.
How Does It Work?
We connect directly to your FNOL intake source, typically a dedicated Microsoft 365 or Google Workspace inbox. Using the Microsoft Graph API or Gmail API, we pull new claims reports in real time. We use the Claude 3 Sonnet API to parse the unstructured text from email bodies and PDF attachments, extracting entities like policy number, claimant name, and a description of the loss.
The extracted data is sent to a FastAPI endpoint running on AWS Lambda. This Python service contains the core logic. First, it standardizes the extracted information. Then, a second call to the Claude API scores the claim's severity on a 1-10 scale based on your agency's custom criteria. We write every parsed claim and its AI-generated score to a Supabase Postgres database for logging and auditing.
The FastAPI service then pushes the data into your AMS. For systems like Applied Epic or Vertafore, we use their supported APIs or webhooks to create a new claim record. The system includes a summary, the severity score, and recommended next steps. Routing logic assigns the claim to the right adjuster's queue. The entire process from email arrival to AMS entry takes under 30 seconds.
For claims scored above a 7/10 severity, the system requires human review. It posts a message to a specific Slack channel with a link to the claim and buttons to "Approve" or "Re-assign". This human-in-the-loop step prevents high-stakes errors. The full system runs for less than $50 per month in AWS Lambda and Claude API costs for an agency handling 300 claims per month.
What Are the Key Benefits?
First Response in Minutes, Not Hours
Reduce average FNOL response time from over 4 hours to under 15 minutes. High-severity claims get attention immediately, not after manual review.
Pay for Results, Not Per-Seat
A one-time build cost with minimal monthly hosting fees. No recurring SaaS license that penalizes you for growing your team of adjusters.
You Own The Code and The Logic
Receive the complete Python source code in your private GitHub repository and full documentation. The system is yours to modify or extend.
Alerts Before Problems Escalate
We set up CloudWatch alarms that trigger Slack alerts if the API error rate exceeds 1% or processing latency passes 60 seconds.
Integrates With Your Current AMS
The system connects directly to Applied Epic, Vertafore, and HawkSoft via their native APIs. No need to change your core agency platform.
What Does the Process Look Like?
Week 1: Scoping and Access
You provide read-only access to your claims inbox and a sandbox environment for your AMS. We map your current triage rules and routing logic.
Weeks 2-3: Build and Test
We build the core parsing and routing engine. You receive a link to a staging environment to test with sample claims and validate the logic.
Week 4: Deployment and Integration
We deploy the system on AWS Lambda and connect it to your live AMS and inbox. You receive the full source code and system documentation.
Weeks 5-8: Monitoring and Handoff
We monitor system performance and AI accuracy for 30 days post-launch. After this period, you receive a runbook for ongoing maintenance.
Frequently Asked Questions
- How much does a custom claims triage system cost?
- Pricing depends on the number of intake sources and the complexity of your routing rules. A typical engagement for an agency with one email inbox and straightforward routing is a fixed project fee. We provide a detailed quote after a 30-minute discovery call where we map out the exact workflow and integration points.
- What happens if the AI misinterprets a claim?
- Every AI decision is logged with a confidence score. For high-severity claims, we build a human review step where an adjuster must approve the routing in Slack. For lower-severity errors, adjusters can manually re-assign the claim in your AMS. The system is built to fail safely and keep a human in the loop for critical decisions.
- How is this different from using the automation in Vertafore WorkSmart?
- Vertafore WorkSmart relies on Optical Character Recognition (OCR) and predefined templates. It struggles with varied email formats and unstructured text. We use a large language model (Claude 3) that understands context, not just keywords or document structure. This allows it to handle any FNOL format without pre-built templates, resulting in much higher accuracy.
- What if our claims intake process changes?
- Since you own the code, modifications are straightforward. A common change is adding a new claim type or adjusting severity scoring criteria. This is typically a few hours of development work. We can handle these updates on a small retainer or you can have any Python developer make the changes using the provided documentation.
- What are the ongoing hosting costs?
- The system runs on serverless infrastructure. For an agency processing up to 500 claims a month, the combined monthly cost for AWS Lambda, Supabase, and Claude API calls is typically under $50. This is significantly lower than any per-seat SaaS tool with comparable functionality. You pay the cloud providers directly, so there is no markup.
- How secure is our claims data?
- Data is encrypted in transit and at rest. We use AWS services that are HIPAA eligible and connect to your systems via secure APIs. The AI models we use, like the Claude API, do not train on your data. The system is deployed within your own cloud environment or ours, with access controls limited to essential personnel.
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