01
AI/ML-powered Medical Coding Tool
Solving the Impossible Triangle: Quality, Customization and Scale in Medical Coding
Building for scale is hard. Building for customization is harder. Building for both without losing quality is where most systems collapse.
Our team designed a medical coding engine used by 10k+ coders across diverse client configurations. It needed to:
1. Adapt to client-specific coding guidelines
2. Maintain industry-grade accuracy
3. Scale across millions of data and users
We built an architecture that made all three non-negotiable:
- A plug-in model for client rules—allowing dynamic rule sets per payer
- Shared services for NLP, audit, and review—centralized for consistency
- Workflow isolation and load-balanced queues—ensuring coders never felt system drag
The result? The product scaled with zero performance loss, supported custom workflows per client, and maintained best-in-class quality.
02
The Chart Retrieval Solution
Solving Retrieval at Scale Without Breaking Trust
Medical record retrieval isn’t just a tech challenge—it’s a human one. Payers want completeness. Providers want low friction. Our architecture had to serve both.
We designed a retrieval solution that brought transparency and scale to the chaos:
- Orchestration Layer: Routed requests based on provider responsiveness, expected value, and SLAs
- Data-Driven Targeting: Used historical retrieval success data to optimize batch prioritization
- Client Alignment Tools: Real-time dashboards and APIs gave clients visibility without overwhelming ops
- Provider-Sensitive Flows: Enabled “soft” touch retrieval before triggering escalations
What made this endure? The platform was built on the idea that people, process, and platform are inseparable. Every architectural decision was made to balance automation with empathy. It’s still running. And still evolving.
