Healthcare evidence intelligence for faster, more traceable review.
CareLayer AI turns fragmented clinical and financial documents into structured, traceable evidence for health insurance claims and pre-authorization workflows — helping human reviewers find gaps, inconsistencies, and supporting evidence faster.
Initial Market: Claims & Pre-Authorization
Hospital insurance teams often coordinate information across claim forms, discharge summaries, bills, laboratory reports, diagnostic reports, and policy documents. When information is incomplete or inconsistent, the result can be repeated payer queries, additional documentation requests, discharge delays, and manual rework.
Our Approach
CareLayer AI provides an evidence intelligence layer that works alongside existing hospital and payer workflows. It analyzes multiple documents belonging to the same healthcare case, extracts relevant clinical and financial facts, correlates supporting evidence, and highlights missing, inconsistent, or potentially unsupported information for human review.
The current MVP has been exercised against real-world claim documentation and refined using feedback from an experienced health-insurance claims practitioner. We are now seeking design partners for controlled workflow evaluation and pilots.
Seeking Design Partners
We are looking to work with a small number of TPAs, health insurers, hospitals, and healthcare operations teams that are willing to evaluate the workflow against representative cases. The goal is to quantify where evidence intelligence can reduce manual correlation, avoidable queries, and review friction.
Founder Background
CareLayer AI is led by Murali Nidugondi, a senior healthcare technology leader with 28+ years of experience designing and modernizing enterprise platforms across healthcare, distributed systems, cloud-native architecture, and AI-enabled systems.
Murali has worked with Siemens, Cerner, and Oracle Health, serving in roles such as Solution Architect, Platform Lead, Architect, and Team Lead.
Prototype & Platform Demos
Our prototypes explore how fragmented healthcare information can be transformed into structured, explainable evidence for human review while integrating with existing healthcare systems.
From Hospital Documents to a Unified Evidence View
A working MVP that analyzes multi-document claim packages and creates a structured evidence view for human review. It demonstrates discharge-summary-led synthesis, bill-to-clinical evidence mapping, diagnosis normalization, cross-document identity checks, gap detection, and pre-authorization-to-discharge comparison.
NHCX Interoperability Platform — Technical Walkthrough
How CareLayer AI connects healthcare data sources using FHIR R4, HL7, and X12. Demonstrates healthcare data transformation, intelligent workflow routing, and standards-based integration across prior authorization and claims workflows.
CareLayer AI — Platform Overview
A concise overview of the CareLayer AI platform — problem framing, solution architecture, workflow validation, AI-assisted reporting, and governed healthcare automation. Built for healthcare leaders, design partners, and technology teams.
Product Engineering
In addition to our healthcare product work, CareLayer provides architecture-led product engineering for startups and growing companies building complex software. Engagements can span architecture, backend platforms, APIs and integrations, cloud modernization, and AI-enabled applications.
Why Now
AI is lowering the barrier to building intelligent software, but the real advantage comes from understanding the right problems, workflows, data, users, and constraints. CareLayer AI is focused on combining deep healthcare technology experience with practical execution.
Tell us what you are trying to improve or build. We will tell you candidly whether CareLayer can help.