"This collaboration represents an important opportunity to apply agentic AI to one of the most complex operational challenges in healthcare," said Amber Nigam, CEO of Basys.ai. "Program integrity requires systems that can interpret complex medical documentation while maintaining accuracy, transparency, and alignment with regulatory frameworks. Our focus is on leveraging our deep expertise on utilization management and FWA, and building new AI systems that can operate reliably in real healthcare environments."

Basys.ai develops domain-specific AI systems designed to support complex clinical and administrative workflows across healthcare organizations. The company's technology helps healthcare stakeholders interpret policies, analyze medical records, and improve the efficiency of operational processes that traditionally require extensive manual review.

"As the prime contractor for the AI Medical Record Review pilot, ePathUSA is focused on bringing together operational expertise and advanced AI capabilities to support CMS's program integrity mission," said Hari Nallure, President of ePathUSA. "Our collaboration with Basys.ai allows us to combine innovative AI technologies with practical implementation experience to evaluate how AI can improve the efficiency, accuracy, and transparency of medical record review."

Through this collaboration, Basys.ai's AI infrastructure is designed to support reviewers in navigating complex medical documentation and policy requirements while maintaining transparency and auditability.

"Medical record review has historically relied on time-intensive manual processes," said Arpan Saxena, CIO of Basys.ai. "Applying domain-specific AI models and structured reasoning frameworks can help reviewers surface relevant clinical information more efficiently while maintaining the transparency required in regulated healthcare environments."

The engagement builds on Basys.ai's growing recognition for its work in applying AI to regulated healthcare workflows. The company was selected as one of the Top 10 finalists from more than 250 submissions in CMS's "Crushing Fraud, Waste, and Abuse" Chili Cook-Off competition, which highlighted innovative approaches to improving program integrity.

Basys.ai's work has also been recognized across the healthcare AI ecosystem. The company has been featured in Gartner's Healthcare AI landscape, highlighting its role in advancing AI-driven healthcare operations. Basys.ai's perspectives on deploying generative AI in regulated environments have also been published in Harvard Business Review, where the company shared lessons from implementing domain-specific AI systems for utilization management and prior authorization.

Basys.ai has contributed to broader conversations on responsible AI deployment in healthcare. Nigam has previously shared the company's perspectives on aligning incentives across healthcare stakeholders and addressing structural challenges in healthcare delivery through forums such as TEDx and discussions hosted by leading academic institutions. Basys.ai has also been invited to participate in conversations on healthcare innovation and data science at The Harvard Chan Studio.

The company's work has been acknowledged across the digital health ecosystem. Basys.ai has been recognized by Rock Health among the Top 50 in Digital Health, highlighting organizations shaping the future of healthcare innovation. The company and its leadership have also been recognized by the Boston Business Journal's 2025, reflecting growing impact across the healthcare technology sector. Basys.ai's work has also been highlighted in several industry forums and publications, including STAT News, reflecting increasing attention to the role of reliable AI systems in regulated healthcare environments.

Basys.ai continues to focus on developing agentic AI systems designed for complex healthcare operations, combining policy interpretation, medical record analysis, and explainable decision workflows while maintaining reliability and compliance with healthcare regulatory frameworks.

"Healthcare is entering a phase where AI will increasingly support complex operational decisions," Nigam added. "Our objective is to build agentic AI systems that healthcare institutions and regulators can trust - systems that improve efficiency while maintaining the transparency and accountability required in public healthcare programs."