Healthcare has a money problem that does not always show up in the exam room. A patient gets treated, the provider submits the claim, and then the payment should follow. In reality, that process often turns into a long trail of insurance portals, denied claims, missing documents, appeal letters, phone calls, and follow-ups that can drag on for weeks or months.
That is the problem Michal Miernowski is trying to solve through Amperos Health.
As the Co-Founder and CEO of Amperos Health, Michal Miernowski is building an AI-powered company focused on denial management, claims recovery, and revenue cycle automation. The goal is not just to make billing teams faster. It is to help healthcare providers get paid for care they have already delivered, without forcing staff to spend their days chasing insurers across disconnected systems.
For many clinics, specialty groups, and provider networks, denied claims are not a small back-office headache. They affect cash flow, staffing, patient access, and the financial stability of the organization. Amperos Health sits right inside that pain point, using AI agents and billing expertise to help providers recover revenue that might otherwise be delayed, written off, or left untouched.
Who is Michal Miernowski
Michal Miernowski is best known as the Co-Founder and CEO of Amperos Health, a healthtech company building AI tools for healthcare revenue recovery. His work is focused on one of the least glamorous but most important parts of healthcare operations: getting claims paid after care has already been provided.
That focus matters because healthcare billing is full of friction. Revenue cycle teams deal with payer rules, claim edits, changing denial codes, documentation requests, appeal windows, and repetitive follow-up work. Even experienced billers can spend hours moving between payer websites, phone queues, internal systems, and spreadsheets.
Instead of treating this as a simple software problem, Michal Miernowski has built Amperos Health around the real workflow of billing teams. The company’s approach is not just about giving providers another dashboard. It is about helping them take action on denied and unpaid claims from start to finish.
That is what makes the story interesting. Michal Miernowski is not trying to sell AI as a vague promise. He is applying it to a very specific problem that healthcare providers already understand: too much revenue gets stuck between care delivery and insurance payment.
What Amperos Health does
Amperos Health is an AI-native platform for denial management and revenue recovery. In simple terms, it helps healthcare providers work denied and unpaid insurance claims more efficiently.
The company supports revenue cycle management teams by handling tasks such as payer follow-ups, portal checks, insurance calls, corrected claims, documentation requests, and appeals. These are the kinds of jobs that often consume a billing team’s time but still need careful handling because every claim has its own details.
The promise of Amperos Health is practical. Providers can offload repetitive claims work, recover more revenue, and reduce the manual burden on staff. At the same time, human billing experts can still support complex cases where judgment and experience matter.
That balance is important. Healthcare billing is too complicated for a shallow automation tool. A denied claim can involve payer-specific logic, medical records, prior authorization details, eligibility questions, coding issues, or missing paperwork. Amperos Health is built to work through that complexity rather than only flagging problems for someone else to fix.
The healthcare billing problem Michal Miernowski is trying to solve
Denied claims are one of the biggest sources of friction in healthcare finance. When an insurer denies or delays a claim, the provider still has to pay staff, maintain operations, and continue caring for patients. The work has already been done, but the payment is still uncertain.
For revenue cycle teams, that creates a constant grind. Someone has to figure out why the claim was denied. Someone has to check the payer portal. Someone has to call the insurance company. Someone has to gather documents, correct the claim, resubmit it, or write an appeal.
In a perfect system, that would be manageable. In the real world, billing teams are often understaffed. Claim volumes keep growing. Payer rules change. Insurance websites are inconsistent. Phone calls take time. Some denials are never worked at all because teams simply do not have enough hours in the day.
This is the space where Michal Miernowski saw an opening for Amperos Health. The company is focused on helping providers recover revenue that already belongs to them, while also giving billing teams a more scalable way to manage denials.
The problem is not only financial. It also affects the people doing the work. Revenue cycle staff can spend their days stuck in repetitive tasks that are stressful, slow, and hard to scale. When AI can take on some of that burden, experienced billers can focus on higher-value work, harder cases, and better process improvement.
Why denial management is such a costly issue
A denied claim is not just a rejected form. It can trigger a chain reaction inside a healthcare organization.
First, it delays payment. That hurts cash flow, especially for provider groups that depend on steady reimbursement to cover payroll, rent, medical supplies, and other operating costs.
Second, it increases administrative costs. Every follow-up call, portal login, appeal letter, and documentation request takes time. Even if the claim is eventually paid, the provider may spend a meaningful amount of money just trying to collect it.
Third, it creates visibility problems. Leaders may know that revenue is stuck, but they may not know exactly where the bottlenecks are happening. Is the issue coding? Eligibility? Authorization? Documentation? Payer behavior? Without clear data, teams can end up reacting to denials instead of preventing them.
Fourth, it puts pressure on staff. Billing teams are expected to do more with less, often while dealing with high claim volumes and strict deadlines. That can lead to burnout, turnover, and missed recovery opportunities.
This is why denial management has become such a strong use case for healthcare AI. It is repetitive enough for automation to help, but complex enough to require domain knowledge. Amperos Health is building in that middle ground.
How Amperos Health uses AI in revenue recovery
Amperos Health uses AI to work through the claims recovery process in a more active way. Instead of only analyzing claims or producing reports, the platform is designed to help complete the work needed to move claims toward payment.
That can include navigating payer portals, checking claim status, placing insurance calls, preparing corrected claims, helping with appeals, and organizing the next best action for a claim. These are tasks that often sit across multiple systems, which is why they are hard for traditional software to handle cleanly.
The value of AI in this setting is not just speed. It is consistency. An AI system can keep working through repetitive payer workflows without getting tired, distracted, or pulled into other urgent tasks. It can help make sure more claims are touched, more follow-ups happen on time, and fewer recoverable dollars fall through the cracks.
At the same time, Amperos Health does not frame the work as AI replacing every human decision. The company’s model includes subject matter expertise for complex and difficult-to-recover claims. That is a realistic approach because healthcare billing still needs judgment, especially when a denial involves unusual payer logic, medical necessity, records, or appeal strategy.
This is where Michal Miernowski’s approach feels more grounded than the usual AI pitch. He is not simply saying AI will fix healthcare. He is applying AI to a clear operational workflow where providers can measure the result in recovered revenue, faster claim resolution, and reduced backlog.
Amanda and the rise of AI billers
One of the key pieces of the Amperos Health story is Amanda, the company’s AI biller for healthcare denials and collections.
Amanda was built to work alongside revenue cycle teams and take on repetitive claims work that usually slows them down. That includes handling insurance websites, making payer calls, and helping determine the fastest path to reverse a denial or collect on an outstanding claim.
The idea behind Amanda is simple but powerful. Instead of asking a billing team to manually chase every claim, Amperos Health gives them an AI coworker that can help handle high-volume, time-consuming workflows. That allows human staff to spend more time on exceptions, complex cases, patient-facing issues, and process improvements.
This matters because many healthcare providers do not have the luxury of building huge billing teams. Smaller practices, specialty groups, and outpatient networks often need better collection outcomes without constantly adding headcount. AI billers can help close that gap by giving teams more capacity.
For Michal Miernowski, Amanda also shows how specific healthcare AI needs to be. A general chatbot cannot solve denial management on its own. The system has to understand payer workflows, claim logic, medical billing patterns, portal behavior, call scripts, documentation needs, and escalation paths. That is why Amperos Health has focused on building around real billing operations rather than treating claims recovery as a simple automation layer.
Why Michal Miernowski’s approach stands out
The most interesting part of Michal Miernowski’s work is the depth of the problem he chose. Healthcare AI often gets attention for clinical tools, diagnostics, patient engagement, or note-taking. Those areas are important, but revenue cycle management is where many providers feel daily financial pressure.
Denied claims are not new. Providers have been dealing with them for years. What has changed is the level of complexity and the pressure on billing teams. More rules, more systems, more payer friction, and more administrative load have created a problem that is hard to solve with people alone.
Amperos Health stands out because it is trying to manage the full denial and recovery workflow, not just one small piece of it. A tool that only identifies denials still leaves the team with the hardest part: getting the claim fixed and paid. A tool that only creates reports still requires people to take action. Amperos Health is built around action.
That action-first approach is what gives Michal Miernowski’s company a stronger position. The platform is not just helping providers understand their revenue leakage. It is helping them do something about it.
The funding milestone and what it means
In April 2026, Amperos Health announced a $16 million Series A funding round led by Bessemer Venture Partners, with continued participation from Uncork Capital and Neo. The round gave the company more capital to scale its platform, expand its team, and build further agentic capabilities across healthcare revenue cycle workflows.
For Michal Miernowski, this funding milestone is more than a startup headline. It shows that investors are paying close attention to the financial infrastructure of healthcare. The back office is becoming one of the clearest places where AI can create measurable value.
The funding also reflects the size of the market problem. Providers need better ways to manage denials, collections, accounts receivable, and payer follow-up. Health systems and clinics are under pressure to improve margins without adding more administrative complexity. A company that can help recover revenue faster has a direct business case.
That is why Amperos Health fits into a bigger shift in healthcare technology. AI is moving beyond simple productivity tools and into real operational workflows. Denial management is one of those workflows where the outcome can be measured clearly: more claims worked, more dollars recovered, lower cost to collect, and less backlog.
How Amperos Health helps providers recover more revenue
The value of Amperos Health comes from helping providers work more claims with less manual effort. In revenue cycle management, that can make a meaningful difference.
When claims are denied, speed matters. The longer a claim sits unresolved, the harder it can become to collect. Deadlines can pass. Documentation can become harder to track. Staff may move on to newer work. Some claims may never get attention because teams are already overwhelmed.
By using AI to support follow-ups, portal work, calls, corrected claims, and appeals, Amperos Health can help providers keep more claims moving. That means fewer missed opportunities and more consistent recovery.
The platform can also help reduce accounts receivable backlog. A large backlog is not only a finance problem. It is a sign that the team may not have enough capacity to keep up with claim volume. When AI takes over repetitive tasks, human billers can focus on claims that need deeper review.
Another benefit is better visibility. If Amperos Health can show where denials are coming from and what actions are helping recover revenue, providers can start improving the process upstream. That means they can move from reacting to denials toward preventing more of them in the first place.
Why this matters for healthcare teams
For healthcare teams, the impact of denial management is very real. A clinic does not run on good intentions alone. It needs predictable payment to keep doors open, hire staff, invest in care, and support patients.
When revenue gets stuck in denied claims, the pressure spreads across the organization. Finance leaders worry about cash flow. Billing managers worry about backlog. Staff feel stretched thin. Providers may feel frustrated that the business side of care is becoming harder to manage.
Amperos Health matters because it gives teams a way to fight that pressure without simply adding more manual work. AI can take on repetitive payer interactions, while human experts stay involved where experience is needed.
That is a healthier way to think about automation. The goal is not to remove people from healthcare billing. The goal is to stop wasting skilled people on tasks that software can help handle. When billing teams are freed from some of the most repetitive work, they can spend more time on problem-solving, strategy, and patient-related support.
This is the human side of Michal Miernowski’s work. He is building technology for a part of healthcare that often gets overlooked but affects almost everything behind the scenes.
Michal Miernowski’s bigger vision for healthcare administration
The bigger vision behind Amperos Health is not only denial recovery. It is a more efficient healthcare financial system.
Revenue cycle management includes many connected workflows: eligibility checks, prior authorization, claim submission, denial management, appeals, payment posting, collections, and reporting. Each step can create friction. Each delay can affect provider revenue. Each manual process can add cost.
By starting with denials and collections, Michal Miernowski is targeting one of the most painful parts of the cycle. But the same AI-native approach could expand into other areas where teams need help managing payer complexity.
That is why Amperos Health is part of a larger movement in healthcare operations. Providers do not only need better electronic health records or more patient-facing apps. They also need better financial infrastructure. They need tools that understand how money actually moves through the healthcare system.
If Amperos Health can continue proving value in denial management, it could become an important layer in how providers manage revenue recovery more broadly.
What other founders and healthcare operators can learn from Michal Miernowski
There are several lessons in Michal Miernowski’s path with Amperos Health.
The first is to solve a painful problem, not a fashionable one. Denial management may not sound exciting from the outside, but it is deeply important to healthcare providers. When a problem is expensive, repetitive, and widely felt, customers are more likely to care about a better solution.
The second lesson is to build around real workflows. Healthcare is full of edge cases. A product that looks good in a demo may fail when it meets payer portals, messy claims, call queues, and missing documentation. Amperos Health has gained attention because it is designed around the actual work revenue cycle teams do every day.
The third lesson is to combine AI with domain expertise. In healthcare billing, accuracy matters. Judgment matters. Experience matters. AI can make the process faster and more scalable, but it works best when it is shaped by people who understand the field.
The fourth lesson is to focus on measurable value. Providers do not need vague AI promises. They need recovered revenue, lower backlog, faster resolution, and less pressure on staff. Amperos Health is built around outcomes that revenue cycle leaders can understand.
For Michal Miernowski, that practical focus is a major part of the company’s success story. He is building in a space where the pain is real, the need is urgent, and the value of better execution is easy to see.
