Healthcare payment software provider Waystar has unveiled new agentic capabilities within its Waystar AltitudeAI platform. Designed to take autonomous action across complex revenue cycle workflows, the software expansion advances the company’s long-term roadmap toward fully autonomous healthcare financial operations.
Built directly into Waystar’s unified cloud architecture, the agentic capabilities leverage proprietary data spanning more than 7.5 billion historical transactions covering roughly 60% of the U.S. patient population. By uniting payer connectivity with multi-layered artificial intelligence, the system transitions healthcare software from passive analytical insights to automated workflow execution.
Unlocking Automation Across High-Friction Revenue Workflows
Persistent administrative friction-ranging from complex claim denial reworks to labor-intensive clinical documentation audits-continues to strain operational margins across health systems. Waystar AltitudeAI addresses these operational bottlenecks by embedding domain-specific AI agents that interpret data, determine correct policy actions, and resolve administrative exceptions.
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Key functional enhancements introduced in the release include:
Autonomous Claim Resubmission: this feature employs AI agents that analyze rejection and denial of the initial claims. They apply payer rules, make necessary changes to the format, and automatically resubmit the eligible claims. This feature is a game-changer, as it gets rid of the necessity of manual backend work, which not only helps to shorten reimbursement cycles but also brings down accounts receivable days quite a bit.
Revenue Cycle Intelligence with a Conversational Twist: Waystar will now take you even closer to the data with the ability to pose natural language queries directly into the analytics suite. Staff operating the processes can, through conversational prompts, easily drill down to the root causes of the issues and discover performance trends and financial impact as well, without the need of creating report dashboards.
Clinical Documentation with Agentic Help: Clinically related chart reviews of AltitudeAI get much broader in their scope. These AI agents are capable of scanning as many as 30,000 pieces of information within the electronic medical record in just a couple of seconds. They gather clinical evidence at the same time as they come up with high-level recommendations for specialist teams, which will allow the review times to be decreased by approximately 25 percent.
Agentic Patient Financial Engagement: A feature introducing a customer’s financial assistant through AI that can navigate the patient through out-of-pocket expenses. Based on the patient’s data from their health journey, this agent brings clear explanation of the remaining balances and options of how to cover them to the patients. This increases the chance for a financial payment to be made and, at the same time, decreases the number of calls to the customer care department.
“Agentic intelligence is a critical layer for the autonomous revenue cycle,” said Matt Hawkins, Chief Executive Officer of Waystar. “By combining AI with the breadth of our data, payer intelligence, and connected workflows, Waystar increasingly identifies what needs attention and deploys specialized agents to pursue resolution. As the system of action for healthcare revenue cycle, we are helping providers reduce administrative work, accelerate financial outcomes, and fundamentally change how they operate.”
Accelerating Performance from Insight to Execution
Claim denials remain one of the most resource-intensive challenges facing healthcare providers. While payers eventually reimburse approximately 70% of initially denied claims, securing those funds traditionally requires extensive manual research, resubmission tracking, and administrative overhead.
By automating the gap between initial payer responses and claim resubmissions, AltitudeAI helps provider organizations capture lost revenue faster. Furthermore, early deployments of Waystar’s conversational analytics engine demonstrate up to a 75% reduction in data analysis time, allowing revenue leaders to shift focus from manual auditing to strategic financial management.
