AI-Driven Enrollment Automation Cuts Processing Delays by 70%
Client Overview
Client is a not-for-profit Medicare Advantage organization founded in 1977 and headquartered in Long Beach, California. It serves more than 300,000 members across several U.S. states, offering comprehensive healthcare solutions designed to help older adults live healthy and independent lives. During the open enrollment period, they see a surge of paper-based enrollments and higher cycle time.
The Operational Drag Created by Manual Processing
Most enrollment forms required manual intervention before they could be fed into the system, as handwritten submissions posed accuracy challenges during data extraction and conversion.
This led to:
Delays in onboarding
Due to repeated corrections, new members waited longer for activation during already time-sensitive enrollment periods.
Repeated compliance checks
Inconsistent data quality triggered multiple validation and rework cycles. Teams had to re-verify submissions to meet regulatory and compliance requirements.
Additional operational effort
Staff spent significant time interpreting handwritten fields and fixing extraction errors. This increased workload without improving accuracy.
Higher enrollment cycle time
Fragmented handoffs extended the processing timelines. Enrollment cycles grew longer as volumes increased, limiting the ability to scale.
Building the Foundation for a Steadier Workflow
The enrollment process needed an end-to-end automated workflow to reduce the administrative overhead.
To achieve this, the workflow had to:
Pull forms from FTP/SFTP, shared drives, and cloud locations.
Extract typed and handwritten data with highest accuracy.
Validate and classify fields with minimal manual checks.
Map submissions to the structured 130+ field OEC format.
Move output into downstream destinations such as AWS S3.
Maintain transparency to align with audit and governance standards.
A Solution Designed for Real-World Complexity
The Enrollment Processing Engine
Kognitos is one of the neurosymbolic AI platforms that could automate any business process workflow in simple plain English. Indium developed this GTM delivery model around a simple principle: accept the reality of how data enters the enterprise.
The AI system ingests handwritten enrollment forms as raw input and converts them into structured, compliant outputs, with human validation applied at critical phases. The workflow below shows how this comes together.
The Difference Delivered by a 7-Day POC and 98%+ Accuracy
The new workflow rebuilt the enrollment engine end-to-end, delivering measurable improvements in speed, accuracy, and operational load.
Final Takeaway
About Indium
Indium is an Al-driven digital engineering company that helps enterprises build, scale, and innovate with cutting-edge technology. We specialize in custom solutions, ensuring every engagement is tailored to business needs with a relentless customer-first approach. Our expertise spans Generative Al, Product Engineering, Intelligent Automation, Data & Al, Quality Engineering, and Gaming, delivering high-impact solutions that drive real business impact.
With 5,000+ associates globally, we partner with Fortune 500, Global 2000, and leading technology firms across Financial Services, Healthcare, Manufacturing, Retail, and Technology-driving impact in North America, India, the UK, Singapore, Australia, and Japan to keep businesses ahead in an Al-first world.
