Waystar , a provider of leading healthcare payment software, announced the introduction of agentic intelligence to its cloud-native platform. This milestone expands Waystar's innovation roadmap and highlights the differentiated power of Waystar AltitudeAI, fueled by the industry's only data network that unifies proprietary clinical, financial, and administrative intelligence at scale.

Agentic intelligence represents the next evolution of Waystar's platform. The company is advancing its ambitious vision for industry transformation by building the autonomous revenue cycle, powered by a dynamic, end-to-end agentic network that continuously acts within workflows, executes defined tasks, and learns from outcomes with minimal intervention. Fueled by more than 7.5 billion annual transactions and one in three U.S. hospital discharges, Waystar's connected AI ecosystem helps eliminate friction in healthcare payments and activates the right AI at the right time to address providers' most pressing priorities.

"Waystar AltitudeAI prevented billions of dollars in denials last year," said Matt Hawkins, Waystar Chief Executive Officer. "With that momentum, agentic AI built on an unparalleled proprietary dataset accelerates our vision for the industry's first autonomous revenue cycle platform and advances our mission to simplify healthcare payments for providers and their patients."

Waystar AltitudeAI agent-powered workflows will expand the self-learning innovation engine and unlock new capabilities and stronger client outcomes, including the following:

• Expedite prior authorizations through proactive clinical justification to ensure more accurate reimbursement
• Prevent denials through integrated documentation, coding, and charge capture revenue protection to drive faster, more predictable cash flow
• Recommend corrections automatically based on historical denial insights to create clean, accurate, and compliant claims
• Accelerate recovery through intelligence-powered clinical appeals to drive higher productivity with lower costs