Most people assume medical bills are correct. They are not.

In fact, studies suggest that 50–80% of medical bills contain errors. Not small rounding issues, but inflated charges, wrong codes, and services that never happened. Now imagine dealing with that while recovering from surgery.

That was the reality for Angel Onuoha. After multiple knee surgeries, he was hit with over $250,000 in medical bills. He fought them down himself, but the process was slow, stressful, and confusing.

That experience revealed something bigger. This was not just bad luck. It was a system problem. And that is how Avelis Health began.

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The Invisible Leak in Healthcare vs What Avelis Actually Built

Zoom out for a second. Employers and health plans lose tens of billions of dollars every year on claims that should never have been paid. Some estimates put that number above $60 billion annually.

Here is the issue: Most systems only review a small percentage of claims, usually the expensive ones. Everything else slips through. Errors go unnoticed. Money quietly disappears.

Even worse, the tools in place are outdated. Many rely on static rules that cannot keep up with changing billing practices. And the organisations responsible for processing claims are not always incentivised to catch mistakes.

So the system keeps moving. And the leak continues. Avelis did not try to tweak the system. They rebuilt a critical part of it.

At its core, Avelis uses machine learning to audit 100% of medical claims, not just a sample. Every single claim gets reviewed for billing, coding, and contract errors.

No shortcuts. But they did not stop at automation. They added a clinician layer to validate findings. This reduces false positives and ensures accuracy, especially in complex medical cases.

The result is simple. Companies save between 2% and 7% of their annual health plan spend, sometimes more. And they gain visibility into where their money is actually going.

Avelis calls this approach Payment Integrity. It works both before and after payments are made. That means it can prevent bad payments and recover money that has already been lost.

It is less of a tool and more of a financial safety net.

Where It Gets Interesting: Recovery, Not Just Detection

Most companies can spot errors. Very few can recover the money. This is where Avelis stands out.

They built voice AI agents that actually contact healthcare providers. These agents handle follow-ups, push through disputes, and negotiate refunds. They do it at scale and without fatigue.

Think about that for a second. Instead of a small team making calls for weeks, Avelis can run thousands of conversations at once. What used to take months now takes hours.

And when providers push back, the system does not stop. The AI uses data, policy knowledge, and billing logic to respond in real time. It does not guess. It argues with context.

On top of that, Avelis tracks every step of the process. From the first call to final settlement, users can see exactly where funds are and what has been recovered.

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Built by Africans, Solving a Global Problem

Avelis was founded by Angel Onuoha and Ahmad Shehu, two builders with roots in Nigeria.

Before this, they built Zuvy, a fintech company focused on invoice financing. It was later acquired. That experience shows in how they approach problems. They do not just build products. They build systems that move money more efficiently.

Now they are applying that same thinking to healthcare. And they are doing it on a global stage.

This matters because it shifts the narrative. African founders are not only building for local markets. They are stepping into complex industries and fixing problems that affect millions of people worldwide effectively.

Avelis is not chasing headlines. It is fixing a leak most people never see. And in doing so, it is saving companies millions and helping bring a bit more fairness into a system that often lacks it.

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