Automate Policy Renewals for Your Agency

Independent insurance agencies often grapple with repetitive, manual tasks during policy renewals. For many, the process begins with CSRs running reports from systems like Vertafore, Applied Epic, or HawkSoft to identify upcoming renewals. This data is frequently exported to spreadsheets, leading to a disconnected workflow where reminders are manually drafted and sent, and client responses are tracked inconsistently. This method is not only time-consuming, often consuming the first week of every month for CSR teams, but also highly prone to human error, such as missed follow-ups or incorrect data entry. Agency management systems like Applied Epic or HawkSoft provide fundamental task reminders, but they typically lack the configurable, multi-step workflow automation necessary to manage the nuances of the renewal process beyond a simple date trigger. While they can log that an email was sent, they cannot automatically trigger a follow-up if a client fails to click a document upload link or provide the necessary information. This means CSRs must manually track document submissions, identify missing information, and chase clients across dozens or hundreds of policies. Furthermore, general automation tools fall short when confronted with the core challenge of unstructured data. An automated tool can send an email when a policy is 90 days from renewal, but it cannot reliably parse a new driver schedule sent by a client as a blurry phone photo, a PDF scan of a property deed, or an email containing updated business inventory. Extracting specific fields like vehicle VINs, driver's license numbers, property valuations, or changes in coverage limits from these varied and often low-quality documents remains a highly manual and time-consuming bottleneck, preventing the efficient pre-filling of renewal applications.

Syntora would commence an engagement by conducting a detailed discovery and audit of your agency's existing agency management system (AMS) – whether it's Vertafore, Applied Epic, or HawkSoft – and the carrier portals you frequently use. This initial phase defines the most effective integration strategy, prioritizing API connections where available and identifying requirements for web scraping where legacy portals are the norm. The system would connect to your AMS via API or webhooks to establish a live feed of policies nearing their 90-day renewal window, ensuring timely triggers. For each identified policy, a tailored Python script, often utilizing tools like Playwright, would be developed to securely log into the respective carrier portal. This script would retrieve the current policy declaration page and other pertinent policy details. All extracted, structured data would be stored securely within a Supabase Postgres database. A FastAPI service would be designed and implemented to orchestrate automated client workflows. At 90, 60, and 30 days prior to renewal, personalized emails would be dispatched via a service like Postmark. These emails would include secure, unique links for clients to upload necessary documents, such as updated driver schedules or property photos. Upon a client uploading a document, an AWS Lambda function would be triggered. This function would send the document to the Claude API with a meticulously engineered prompt designed to extract specific, required fields, such as vehicle VINs, new driver's license numbers, or updated property valuations. The Claude API typically processes these requests and returns structured data as JSON within a few seconds. Syntora has experience building robust document processing pipelines using Claude API for financial documents, and the same underlying pattern applies directly to insurance documents. This extracted structured data would then be utilized to pre-fill the carrier's renewal application. For carriers offering modern APIs, this would involve a direct POST request to their system. For carriers with web-based portals, the Playwright script would navigate the portal and populate web forms, field by field. This architecture aims to process documents and generate a pre-filled application, ready for agent review, often within minutes. The completed pre-filled application and a concise summary derived from Claude's analysis would be routed to the assigned agent's inbox. To maintain accuracy and compliance, every AI-extracted data point, such as a VIN or a name, would be logged with an associated confidence score. Any extraction falling below a predefined threshold, for example 95%, would be flagged for mandatory human review. This human-in-the-loop process significantly mitigates potential errors. The underlying infrastructure, built on serverless components like AWS Lambda and Supabase, is engineered for efficiency and low operational costs, with typical base usage often under $50 per month. A typical build engagement of this complexity would range from 10 to 16 weeks, with client responsibilities including providing API access, carrier portal credentials, defining specific data points for extraction, and collaborating on user acceptance testing.