If you want to understand what cliexa does, start with the waves.

Mehmet Kazgan, CEO & Founder of cliexa, has spent years tracking the distinct technology cycles that have shaped modern healthcare. First came electronic medical records, digitizing records and billing. Then came interoperability, linking data across systems through the Cures Act. Then came AI scribes, automating documentation. Each wave built on the last. Each one solved part of the problem.

"We worked for about eight years to build a clinical reasoning engine," Kazgan says. "Back in the days, we were building an engine, but without a car frame, it didn't make sense. Now there are a lot of frames, and people are looking for the best engines."

That is precisely where cliexa stands today. Not as another scribe. Not as another interoperability layer. But as the clinical reasoning engine that makes all of those other tools smarter.

The timing could not be better. Following the mainstream emergence of AI tools like ChatGPT, healthcare organizations have stopped asking whether AI can work and started asking whether they can afford to wait. "It's not about the hype," Kazgan says. "It's ‘am I missing an opportunity here?’ Health systems, our customers, prospective customers, they're all looking into doing things themselves, enabling AI, or they're trying to figure out what is the best solution to get."

cliexa's answer to that question has been eight years in the making.

The company's core thesis is captured in its brand positioning: healthcare must move “From Record to Reason.”

Today's clinical environment is sophisticated in some ways and deeply fragmented in others. A provider has access to more data than ever before, yet the pressure of a single encounter leaves little room to synthesize it. A specialist prescribing pain medication may not know that their patient saw a psychiatrist last week and had their depression medication adjusted. A billing team may not understand why a claim was denied if they were not connected to the reasoning that shaped the clinical note. A patient may not know what questions to ask or what their insurance actually covers. The record exists. The reasoning doesn't travel with it.

cliexa runs in the background of all of it simultaneously.

Powered by a dual-LLM architecture and a proprietary Clinical Rules Engine, cliexaAI delivers what Kazgan describes as real-time, explainable clinical reasoning directly within electronic medical records, calibrated to payer requirements, provider protocols, and the specific state of each patient. The platform is both EMR-agnostic and cloud-agnostic, a deliberate design choice that reflects how enterprise health systems actually evaluate vendor relationships.

"Imagine a clinical reasoning in the background," Kazgan says. "This is not a publicly trained model. This is a model that was trained on similar patient populations, but now it's calibrating to your world today, so it starts operating with your benchmarks."

The same brain powers three distinct interfaces at once: the patient-facing onboarding and monitoring layer, the provider-facing clinical encounter layer, and the administrative billing layer that ensures documentation supports medical necessity. cliexa sits at the intersection of these three realities that rarely speak to each other: what payers require, what providers document, and what patients actually experience. By connecting these three, it transforms the static record into something dynamic, not just a chronicle of what happened.

"You cannot reason without having a brain in the background," Kazgan explains. "Doctors are great, but they cannot operate 300,000,000 formulas and pattern recognition in a second."

What cliexa provides is not a decision. It is a picture. One that makes it possible for the right decision to be made with confidence.

Building a clinical reasoning engine is one thing. Getting it validated by institutions that have spent decades setting the standard for evidence-based care is another.

cliexa has done both.

Mayo Clinic Platform, the digital health marketplace arm of Mayo Clinic, completed a rigorous qualification process and has validated  cliexa's Opioid Use Disorder Prediction Platform. The solution is now live and white-labeled within Mayo's platform network, available to any health system in their ecosystem with the equivalent ease of downloading a vetted app.

"It's because it's been tested and validated and the payment system is there," Kazgan says. "Mayo Clinic Platform is our reseller, offering the solution to their network of hospitals."

The opioid use disorder tool matters because the clinical gap it closes is real and consequential. When a dentist prescribes oxycodone after a procedure or an orthopedic surgeon recommends pain management after a knee replacement, they are doing their job. But if that patient is already on SSRIs, already experiencing depression, or already carrying risk factors the provider does not have visibility into at that moment, the outcome can be catastrophic. cliexa surfaces those indicators in real time, at the point of prescribing, before a note is finalized and before a prescription is written.

The American College of Cardiology represents a different but equally significant kind of validation. They have not just endorsed cliexa – they have co-developed cardiovascular clinical algorithms with the company and invested in it. According to Kazgan, cliexa is the first and only company the American College of Cardiology has both invested in and co-developed a technology with. Key contributing cardiologists include John Rumsfeld and Dipti Itchhaporia.

These are not marketing relationships. They are proof that cliexa's clinical reasoning holds up under the scrutiny of institutions that cannot afford to get it wrong.

If you want to see clinical reasoning under pressure, look at eating disorders.

A single patient receiving care at a facility like Eating Recovery Center (ERC Pathlight), which operates 36 locations with more than 1,000 providers, may be seen by a psychiatrist, a nutritionist, a pediatrician, and other specialists, all contributing to a single coordinated treatment plan. Each encounter happens at a different level of care. Each provider has a different documentation requirement. The patient may be a minor. The payer may be Medicaid. The acuity shifts. The stakes are high in every direction.

"It's a very complex treatment methodology," Kazgan says. "What we're doing with Eating Recovery Center is we put the brain behind the scenes."

Within their EMR, cliexa tracks the conversation across providers and levels of care, ensures that each note reflects the appropriate clinical and payer requirements for that specific context, and generates documentation that meets what Kazgan calls the acuity of coverage. Not just transcription. Not just automation. Reasoning.

A peer-reviewed research paper on AI and eating disorder clinical care, developed in partnership with Eating Recovery Center, has been approved and is expected to be published imminently. It will represent another layer of independent validation for the platform.

Perhaps the most striking thing Kazgan says in conversation is also the most grounded.

"We're not replacing systems, people, or workflows. We optimize them."

This is not a pitch. It is an architecture decision. cliexa was built from the beginning to embed within existing infrastructure, not to disrupt it. The clinical reasoning engine does not require a new EMR or a new patient portal. It operates within what health systems already have and makes every piece of it more intelligent.

That positioning matters for health systems that have spent years and significant capital building out their current technology environments. cliexa does not ask them to start over. It asks them to imagine what those environments could do with a reasoning layer running underneath.

The traction is real. cliexa has $3.2 million in contracted ARR and is profitable. The model has been trained on more than 12 million patient data points. And a major government and federal partnership announcement is expected in the near term, expanding cliexa's clinical intelligence into new populations and new settings.

"The window to partner or invest before this scales is now," Kazgan says. "We have customers. We have validation qualifications. We have papers waiting to be published."

The arc of cliexa's story follows the same logic as the clinical reasoning engine itself: building steadily, validating rigorously, and moving at the pace of evidence.

The next chapter involves continued expansion in government and federal healthcare. New research publications are on the horizon. And for health systems evaluating the next wave of AI investment, Kazgan has a clear message.

"If you're investing in AI scribes, billing tools, or patient engagement platforms and they're not connected to a clinical reasoning engine, you're automating the wrong things. cliexa is the brain those tools are missing."

For the broader health innovation community, cliexa's progress is a signal worth paying attention to. Clinical AI is not just about efficiency. It is about reasoning. About closing loops. About ensuring that everything happening around a patient, from prescription to payer to provider, is connected to the same intelligence in real time.

That is the future cliexa is building – and we are proud to have Mehmet Kazgan as a member of the StartUp Health community.