Replace Fragile Insurance Workflows with Production Python Code
Custom Python automation replaces no-code tools for insurance policy management. It handles complex logic, high data volume, and direct carrier portal access.
Building a custom system is for agencies whose core operations, like claims intake or renewal processing, are too critical to run on generic platforms. The scope depends on the number of integrations. Connecting to a modern Agency Management System with a documented API is straightforward. Automating data extraction from five different carrier portals without APIs requires more complex engineering.
We built a claims triage system for a 6-adjuster agency that was drowning in FNOL emails. The Python service we deployed uses the Claude API to parse, score, and route incoming claims. It cut their average first-response time from 4 hours to 12 minutes within the first week of operation.
What Problem Does This Solve?
Agencies often start with visual workflow builders to connect their email to their Agency Management System (AMS). These tools are great for simple notifications, but they fail when faced with the specific logic of insurance. A renewal workflow that needs to check policy status, generate a reminder, parse an attached document, and update the AMS can burn 5-10 tasks per policy. For an agency managing 2,000 policies, that's a high monthly bill for a single process.
These platforms also struggle with state management and error handling. If a carrier's API is slow and a connection times out mid-workflow, the entire process often fails silently. An adjuster only discovers the missed renewal when the client calls. There is no built-in logic to retry the connection or route the failure to a human for review. The result is a system that requires constant manual monitoring, defeating the purpose of automation.
The pre-built connectors are convenient but brittle. When a carrier updates its portal, a generic integration can break for days until the platform provider issues a patch. This is not acceptable for business-critical functions like claims processing. These tools cannot handle the conditional complexity or provide the reliability required for managing policies and claims at scale.
How Does It Work?
We start by connecting directly to your Agency Management System (Applied Epic, Vertafore, HawkSoft) via its API or webhook capabilities. For carrier portals without APIs, we build secure data extractors with Playwright that run on a schedule. All data, from policy details to FNOL reports, is normalized into a consistent JSON format and stored in a Supabase Postgres database. This initial data sync typically covers the last 24 months of activity.
The core of the system is a set of Python functions deployed on AWS Lambda and exposed via a FastAPI interface. For claims intake, an incoming FNOL email triggers a Lambda function. We use the Claude API to parse the unstructured text, extract entities like policy number and incident details, and generate a concise summary. The system scores claim severity on a 1-10 scale. This entire process, from email receipt to structured data in Supabase, completes in under 900ms.
The structured claim data is then posted back to your AMS. Claims with a severity score over 7 trigger a real-time notification in a dedicated Slack channel for senior adjusters. The alert includes the AI-generated summary and recommended next steps. All external API calls use the httpx library for asynchronous requests with automatic retries, and all actions are logged using structlog for easy debugging.
Every AI decision is logged with a confidence score. For high-stakes actions, we build a human review gate using a simple Vercel frontend. An adjuster must approve any AI-routed claim with a confidence score below 95% before it's finalized. We monitor the entire system with AWS CloudWatch, with alerts configured for latency spikes over 2 seconds or any increase in the API error rate.
What Are the Key Benefits?
Cut Response Time from Hours to Minutes
Our claims triage system for a 6-adjuster agency reduced average first-response time from 4 hours to 12 minutes by automating FNOL parsing and routing.
Pay for Compute, Not Per-Task
A renewal workflow processing 1,000 policies a month costs under $20 in AWS Lambda fees, not hundreds on a task-based subscription platform.
You Get the Keys and the Blueprints
You receive the full Python source code in your private GitHub repository, plus deployment scripts and a detailed runbook. You own the entire system.
Alerts Before Your Team Sees a Problem
We configure CloudWatch alarms that trigger on API errors or high latency. You get a Slack notification if a carrier portal connection fails.
Connects Directly to Your Core AMS
Native API and webhook integrations with Applied Epic, Vertafore, and HawkSoft. No more manual data entry or fragile CSV imports between systems.
What Does the Process Look Like?
System & API Access (Week 1)
You provide read-only API credentials for your Agency Management System and key carrier portals. We receive a walkthrough of the current manual process.
Core Workflow Build (Weeks 2-3)
We build the data processing pipeline in Python and deploy the FastAPI service. You receive a technical design document and access to a staging environment.
Integration & Testing (Week 4)
We connect the system to your live AMS and third-party services. You receive a testing plan to validate a batch of 50-100 real policies or claims.
Launch & Monitoring (Weeks 5-8)
The system goes live. We monitor performance and accuracy for 4 weeks. You receive the final source code, documentation, and runbook for handoff.
Frequently Asked Questions
- What factors determine the cost and timeline?
- The primary factors are the number of systems to integrate and the complexity of the business logic. A single claims triage workflow connecting an email inbox to an AMS takes about 4 weeks. A multi-carrier policy comparison tool requiring custom web scrapers for 5 different portals could take 8-10 weeks. We provide a fixed-price proposal after our discovery call.
- What happens when a carrier's portal changes and a scraper breaks?
- The scraper is built to fail gracefully. It logs the error to CloudWatch, sends an alert, and stops processing for that carrier only. Other workflows are unaffected. We typically deploy a fix within 24-48 hours. This is covered under an optional monthly maintenance plan, which begins after the initial 8-week launch period and monitoring phase is complete.
- How is this different from hiring a managed services provider (MSP)?
- MSPs manage your existing software configurations. They might set up email templates or user permissions in Applied Epic. Syntora builds new software from scratch that sits on top of your AMS to perform tasks the AMS cannot, like using an LLM to parse unstructured claim reports or automatically comparing policy documents from competitor portals.
- How is our sensitive policyholder information handled?
- Data is encrypted in transit using TLS 1.2+ and at rest using AES-256. We use AWS Secrets Manager for all API keys and credentials, never hardcoding them. Our Supabase instance can run in your own dedicated AWS account, giving you full control over data access and residency. We sign an NDA before any engagement begins.
- What happens if we migrate from Vertafore to Applied Epic?
- Because the core business logic is separate from the AMS integration layer, migration is straightforward. We would write a new integration module for Applied Epic while the Vertafore module continues to run. This is a small, scoped project. The core FastAPI application and Claude-based parsing logic would not need to be rebuilt, saving significant time and cost.
- How do you ensure the AI's output is accurate for claims?
- We use the Claude 3 Sonnet model for its high accuracy in extraction tasks. Every AI-generated summary and severity score is logged with a confidence level. For critical workflows, we implement a human-in-the-loop step where an adjuster must approve any AI decision with a confidence score below 95% before it is finalized in the AMS.
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