Claims, made actionable.
From mixed claim packets to typed facts, visible exceptions, reviewer-ready decisions, and auditable workflow state.
≈90% lower handling effort in a measured packet workflow
Senior Applied AI / ML Engineer
Healthcare & insuranceShailesh Dudala.
I turn complex data into AI systems
people can put to work.
Production agentic AI, predictive ML, and document intelligence. Built with the care real operations demand.
Explore selected work01 / Selected work
All professional work Built around real problems.
Better predictions. Better care.
Readmission, length-of-stay, utilization, quality, and FWA models designed around calibration, explainability, monitoring, and workflow fit.
18% transportation waste reduction
From models to a product.
A 0-to-1 product connecting risk models, data pipelines, embedded analytics, and care-manager workflows across nine programs.
$500K new revenue supported
Private data. Useful answers.
OCR, retrieval, local inference, citations, and review stayed inside the data boundary while making evidence faster to inspect.
7K-case backlog cleared
Selected outcomes
Across distinct workstreams
case backlog cleared
On-premises compliance review workstream in a healthcare payer environment.
automated closure improvement
Healthcare quality-measure evidence extraction and review workflow.
client P4P impact
Approximate client performance-based payouts supported by the broader program.
02 / In the open
Explore projects A closer look at the engineering.
03 / A little contextResearch trained me to ask.
Research trained me to ask.
Engineering taught me to build.
My work spans biomedical informatics, healthcare analytics, private document systems, and production agentic AI. The thread through all of it: understanding the decision, then building the system that makes it possible.
Team recipient, 2025 Global HL7 AI Challenge
Let's Talk Doc · Transformative Impact in Healthcare
Have something in mind?
Get in touch