AI case study

OneAssurePolicy processing

Hand-keying 30 fields per PDF took 10 minutes—payout errors frayed advisor trust. Document AI now handles each in under a minute.

Published

Key results

Policy Processing Time
< 60 secs
vs 10-minute manual data entry
Monthly Lead Generation
150-200
Extraction Accuracy Gain
98%

Result highlights

Unlock 5 result highlights

The story

Context

An Indian insurtech platform simplifying health insurance with a digital-first approach, growing at 1,000 new users per month with nearly half its business flowing through offline channels and a network of over 250 advisors.

Challenge

A lean operations team manually entered data into up to 30 fields per document from complex PDFs mixing images and text, a process that took 10...

Solution
Unlock full story

Scope & timeline

  • 20% increase in active users from AI tools

Quotes

Unlock 1 more quote

The company

OneAssure logo

OneAssure

oneassure.in

Online health and term insurance advisory and distribution platform.

IndustryInsurance
LocationBengaluru, Karnataka, India
Employees11-50
Founded2020

The implementation partner

Role in this case study

Guided OneAssure on optimizing Gemini model parameters for precise insurance data extraction.

IndustryTechnology
LocationBengaluru, KA, India
Employees11-50
Founded2023

The vendor

Cloud computing services, AI infrastructure, and data analytics platforms for enterprises.

IndustryTechnology
LocationMountain View, CA, USA
Employees100K+
Founded1998

Use case

OneAssure's Policy processing is part of this use case:

Data Extraction
137 case studies(-5% YoY)
Proven impact?
Average
4.0Typical
4.0Typicalwithin Insurance
4.0Typicalwithin Operations

Similar Case Studies

Related implementations across industries and use cases

137 AI case studies in Data Extraction

89 AI case studies in Insurance

336 AI case studies in Operations