Implement an AI-Driven Onboarding Process for New Insurance Clients

Most agencies rely on their Agency Management System (AMS), like Applied Epic or Vertafore, for client management. However, the initial data entry remains a severe bottleneck. New clients might fill out a web form using a tool like Jotform or a fillable PDF, but that data does not flow automatically into the AMS. This disconnect forces an account manager to manually re-type every piece of information.

Consider a 10-person independent agency onboarding a new commercial client. The client returns a 12-page PDF application. An account manager then spends 45 minutes transcribing the business name, address, EIN, and specific coverage details into Applied Epic. A single mistyped digit in an EIN can cause compliance and quoting failures down the line. This manual transcription is repeated for every new client, consuming dozens of skilled labor hours each month.

The structural problem is that general-purpose form builders are not designed for insurance data. They cannot validate industry-specific fields found on ACORD forms. While AMS platforms have data import functions, they demand perfectly formatted CSV files, not the messy PDFs and varied web form submissions that agencies actually receive. A critical translation layer is missing, one that can intelligently read an unstructured document and transform it into the rigid format the AMS requires.

Syntora's engagement would begin with a detailed audit of your current client intake process. We would review all your new client application forms and map every required data field to its corresponding entry in your AMS, whether it is Applied Epic, Vertafore, or HawkSoft. This discovery phase produces a complete data dictionary and a process flow diagram, which you approve before any code is written.

The core of the solution would be a custom API built with Python and FastAPI. When a new client submits their application, the document is sent to this API. The system uses the Claude API to parse the text and structure the data into a clean JSON format. We have used this exact pattern for processing complex financial documents, and the same logic applies to insurance applications. Pydantic models then validate the extracted data against your approved data dictionary, ensuring every field is correct before it reaches the AMS.

The delivered system is a secure AWS Lambda function that connects directly to your AMS. Your team's workflow changes from data entry to data verification. They receive a notification that a new client record has been pre-filled and their task is simply to review it. This system would reduce manual entry time from 45 minutes per client to under 2 minutes. You receive all source code, a maintenance runbook, and a dashboard to monitor processing volumes.