300K auto policies processed each year 150+ underwriting and claims staff 6-state footprint across New England Manual re-keying slowed every quote and raised error risk. Some of the issues that had cropped up include: PDFs and scanned forms forced staff to retype names, VINs, and coverage data Quote packages often took hours to reach agents and brokers Typos in coverage limits triggered costly endorsements and claim disputes Impact Delivered Model fills every field the moment a to onboard new event types, from New agents issue bindable quotes in We inserted an AI extraction layer that drops clean data straight into core systems. Here are some of the features: An Azure function fires on each upload and routes files to processing Captures names, addresses, vehicle details, VINs, and coverage in seconds Pandas, Regex, and NumPy tidy fields and build a structured JSON record JSON flows to policy-admin and quoting tools through azure API management No hardware to maintain; scaling happens automatically Business Case
Document silos
Long turnarounds
Error fallout
80% less manual
entry time
file arrives90% fewer key-in
errors
weeks to days3x faster quoteturnaround
under ten minutes Our Solution
Event-driven ingest
Custom Form Recognizer model
Python post-processing
Secure API hand-off
Serverless design
Tech Stack
Azure Form Recognizer
Python
Azure Functions
NumPy
Pandas
Azure API Management
