Waystar Launches Agentic AI Solutions to Transform Healthcare Revenue Cycle Management
Waystar, a healthcare payment software provider, has announced a new set of agentic artificial intelligence capabilities designed to move healthcare revenue cycle management from automated insights toward autonomous action.
The new capabilities are powered by Waystar AltitudeAI and are designed to take action across several critical revenue cycle workflows, including claims resolution, financial analytics, clinical documentation and patient financial engagement. The company says the latest innovations represent another step toward its broader vision of an autonomous revenue cycle in which artificial intelligence can identify issues, determine appropriate next steps and execute eligible actions with limited human intervention.
The solutions are built on Waystar’s healthcare payment platform, payer connectivity and proprietary data infrastructure. The company says its network spans more than 7.5 billion transactions and approximately 60% of patients in the United States, providing a broad data foundation for its AI capabilities.
According to Waystar, combining AI with payer intelligence, connected workflows and healthcare revenue cycle data can help providers reduce administrative workloads, accelerate reimbursement and improve financial performance.
“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.”
The company’s latest AltitudeAI capabilities are focused on turning AI-generated insights into practical actions across healthcare organizations.
Moving AI From Insights to Action
Artificial intelligence has increasingly become part of healthcare organizations’ efforts to automate administrative processes and analyze operational data. However, identifying an issue is only one part of solving it.
Waystar’s latest approach focuses on what happens after an AI system identifies a problem.The company’s agentic capabilities are designed to analyze information, determine the appropriate response and, in certain workflows, take action automatically. This model could reduce the number of manual steps required from revenue cycle teams and allow staff to focus on more complex cases.
For healthcare providers managing thousands or millions of transactions, even relatively small improvements in administrative efficiency can have a significant effect on overall operations.Waystar is positioning its agentic AI technology as a system of action for revenue cycle management, with applications that extend from the initial claim through payment and patient financial interactions.
Autonomous Claim Resolution
One of the most significant additions is Waystar’s autonomous claim resubmission capability.Claim denials and rejections remain major challenges for healthcare organizations. When claims are rejected or denied, staff may need to determine why the payer did not process the claim, identify what needs to be corrected and resubmit the claim.
This process can consume significant staff time and delay reimbursement.Waystar says payers ultimately pay approximately 70% of claims that are initially denied, but providers may have to invest additional time and resources in reworking those claims before payment is received.
The company’s new agentic capability is designed to reduce the manual work involved in eligible claim resubmissions.Waystar agents can interpret responses received from payers and use payer-specific intelligence to determine the next appropriate action. For eligible claims, the system can then automatically resubmit the claim with minimal human intervention.
This approach is intended to shorten the time between receiving a payer response and taking action.By automating eligible resubmissions, healthcare organizations may be able to reduce administrative delays, limit repetitive work and improve accounts receivable performance.
The technology is particularly relevant to organizations dealing with large claim volumes, where manually reviewing every rejected or denied claim can place significant pressure on revenue cycle teams.
Reducing Administrative Burden in Claims Management
Claims management involves multiple steps and often requires revenue cycle professionals to interpret information from different sources.Payer rules and requirements can vary, adding another layer of complexity. A process that works for one payer may not necessarily apply to another.Waystar’s claim resolution agents are designed to incorporate payer-specific intelligence into their decision-making process.
Rather than simply identifying that a claim has been denied, the technology is intended to interpret the payer’s response and determine what action should be taken next.For healthcare organizations, the potential benefit is a more streamlined workflow in which routine and eligible claim corrections can be handled automatically, while employees concentrate on cases requiring more specialized judgment.This could allow revenue cycle teams to use their time more strategically while maintaining greater focus on complex claims and exceptions.
Conversational Revenue Cycle Intelligence
Waystar is also introducing conversational AI capabilities within its next-generation analytics tools.Healthcare organizations generate enormous amounts of operational and financial data. However, having access to data does not necessarily mean that organizations can quickly identify why financial performance is changing.Revenue cycle professionals may need to analyze multiple reports, compare trends and investigate different variables to determine the underlying cause of a problem.
Waystar’s conversational AI is designed to simplify this process by allowing users to ask questions about revenue cycle performance using natural language.Instead of manually navigating complex datasets, users can interact with the system conversationally to explore trends, identify potential root causes and understand their financial impact.
This approach could make analytics more accessible to healthcare professionals who may not have advanced data analysis skills.The objective is to help organizations move more quickly from identifying a problem to deciding what action should be taken.
Faster Data Analysis for Healthcare Teams
Waystar says early adopters of its conversational analytics capabilities have reported reductions of up to 75% in the time spent on data analysis.If sustained at scale, improvements of this kind could have significant implications for revenue cycle teams.Financial analysts and operational leaders could potentially spend less time gathering and organizing information and more time addressing the issues identified through analysis.
For example, instead of spending hours reviewing multiple reports to determine why a particular area of revenue cycle performance has changed, users could ask questions directly and use the resulting insights to guide further investigation.The ability to identify trends and root causes more quickly could also help organizations respond to financial challenges before they become larger operational problems.
Expanding Agentic AI Into Clinical Documentation
Waystar is also expanding its use of agentic AI into clinical documentation workflows.Clinical documentation is an important part of healthcare revenue cycle management because documentation can influence coding, claims and reimbursement.
Reviewing medical records can be a time-intensive process, particularly when records contain large amounts of clinical information.Waystar says its agents can analyze approximately 30,000 data points within a medical record in seconds. The system is designed to synthesize relevant clinical information, generate high-confidence recommendations and organize supporting evidence for review by specialists.
This capability builds on clinical agentic solutions that Waystar introduced earlier in the year.The company expects the technology to reduce review time by approximately 25%.By assisting with the initial review and organization of clinical information, the system could allow documentation teams to spend more time on cases that require specialized expertise and professional judgment.
The technology is also intended to support accuracy and appropriate reimbursement by helping teams identify relevant information within complex medical records.
Supporting Clinical Documentation Teams
Healthcare organizations face ongoing pressure to maintain accurate clinical documentation while managing large volumes of patient information.Manual review can create operational bottlenecks, particularly when specialists must examine lengthy records to identify information relevant to documentation or reimbursement.
Agentic AI could help address this challenge by rapidly processing large quantities of information and highlighting the details that require attention.Waystar’s approach is not positioned as a replacement for specialist review. Instead, the system organizes information and provides recommendations and supporting evidence for professionals to evaluate.This model combines automated analysis with human oversight, potentially helping teams complete reviews more efficiently.
Agentic Patient Financial Engagement
Another major component of Waystar’s latest AI expansion focuses on patients themselves.Patient financial responsibility has become an increasingly important issue within the U.S. healthcare system. Waystar says patients now account for more than $556 billion in annual out-of-pocket healthcare spending.
As patients assume a greater share of healthcare costs, organizations need effective ways to communicate financial information clearly and help patients understand their responsibilities.Waystar is introducing an AltitudeAI-powered agentic concierge designed to guide patients through their financial journey.
The system uses information from across the patient’s financial experience to provide more personalized interactions.The goal is to help patients understand key questions, including how much they owe, why they owe it and what steps they can take to resolve their balance.
Creating a More Personalized Financial Experience
Healthcare bills can be difficult for patients to understand, particularly when they involve insurance coverage, deductibles, coinsurance, multiple providers or different services.A generalized financial communication may not adequately address an individual patient’s questions.
Waystar’s agentic concierge is designed to use context from the patient’s financial journey to provide more relevant interactions.
By delivering information based on a patient’s specific circumstances, the technology could help make financial communications easier to understand.For healthcare organizations, automated patient financial engagement could also reduce the number of routine questions handled manually by administrative teams.
Employees could potentially spend less time responding to basic balance and payment questions while patients receive more immediate access to information.
Building Toward an Autonomous Revenue Cycle
The four new capabilities—autonomous claim resolution, conversational revenue cycle intelligence, agentic clinical documentation and agentic patient financial engagement—represent different applications of the same broader strategy.Waystar is working toward a revenue cycle environment where AI does more than provide recommendations.
The company’s vision is for AI agents to identify what requires attention, understand the relevant context and take appropriate action within connected workflows.Such an approach could transform revenue cycle operations by reducing the amount of manual intervention required for routine processes.
At the same time, human expertise would remain important for complicated cases, exceptions and decisions requiring professional judgment.
Using Data and Payer Connectivity
Waystar’s AI strategy is supported by the company’s extensive transaction data and payer connectivity.The company says its proprietary data spans more than 7.5 billion transactions and approximately 60% of U.S. patients.This scale provides a substantial source of information for developing and powering revenue cycle intelligence.
Payer connectivity is also important because claims, payment and reimbursement processes depend heavily on interactions between healthcare providers and insurance organizations.By combining payer intelligence with AI and connected workflows, Waystar aims to create systems that can respond more effectively to payer-specific requirements.This could be particularly valuable as healthcare organizations continue to navigate complex reimbursement environments.
Demonstrating the Technology to Healthcare Leaders
Waystar is showcasing its latest innovations during its Fall Innovation Showcase as part of Waystar True North™, the company’s annual client conference.More than 600 healthcare experts are attending the conference to examine developments in healthcare revenue cycle technology and discuss the industry’s movement toward more autonomous operations.
The event provides an opportunity for healthcare organizations to explore how AI can be applied to practical administrative and financial challenges.Rather than focusing exclusively on AI as an analytical tool, Waystar’s latest offerings emphasize execution—using AI to complete tasks that traditionally required human intervention.
The Future of Healthcare Revenue Cycle Management
Healthcare organizations continue to face pressure to improve financial performance while managing administrative complexity and rising patient expectations.Revenue cycle management sits at the intersection of clinical documentation, payer interactions, reimbursement and patient financial responsibility. Because these processes generate large amounts of structured and unstructured data, they represent an area where AI and automation could have significant operational impact.
Waystar’s latest agentic capabilities are designed to address these challenges by connecting intelligence with action.Automated claim resubmission could help reduce rework. Conversational analytics could accelerate financial analysis. Agentic clinical documentation could reduce review time. And AI-powered patient engagement could provide more personalized financial support.
Together, these capabilities support Waystar’s broader objective of creating an autonomous revenue cycle.As healthcare providers continue adopting AI, the emphasis is increasingly shifting from simply generating insights to using technology to execute routine tasks and resolve operational issues.
Waystar’s latest AltitudeAI innovations reflect that evolution. By combining agentic intelligence, payer connectivity, healthcare transaction data and connected workflows, the company is seeking to help healthcare organizations operate more efficiently while improving financial outcomes and patient experiences.
The broader impact of these technologies will depend on how effectively healthcare organizations integrate AI into existing workflows, maintain appropriate human oversight and measure improvements in financial and operational performance. However, the move toward agentic revenue cycle management signals a significant change in how healthcare administrative work may be performed in the years ahead.
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