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| Reveali’s Founders discuss the launch on athenaOne

| Reveali’s first sponsored feature with Aging in America News introduced its approach to “Personalized Health Risk Intelligence” — turning everyday behavioral and wellness observations into structured insight that can help care teams see risk earlier.

Since then, the company has reached an enterprise milestone: Reveali’s health risk intelligence platform operates in Athenahealth‘s electronic medical record environment, athenaOne. For health systems, insurers, risk-bearing organizations, and those investors evaluating the next generation of healthcare intelligence, the significance is less about another standalone limited purpose application but rather directly about where the intelligence appears: inside the everyday workflows that the clinicians and other health care providers already use. We sat down with Reveali co-founder and CEO Rick Newton and co-founder Tony Roth to discuss what the athenaOne commercialization means, what it took to build Reveali, and why the path from collecting medical/nonmedical data to actionable clinical intelligence matters.

What does it mean, practically, that Reveali now works inside athenaOne?

Tony Roth: Practically, it means the observational layer of a person’s health — wellness signals, behavioral patterns, changes in routine, and other information that rarely makes it into a traditional chart — can be organized alongside the clinical record for the primary care physician marketplace. Our work focuses on categorizing, analyzing, and informing on the medical and holistic acuity in a personalized report that is stackable, scalable, and useful at the point of care as well as to the insurance and government programs. The enterprise value is straightforward: clinicians should not have to open other platforms or interpret pages of raw data. Reveali is designed to turn data-driven longitudinal observations into concise, decision-supporting context that can be reviewed within the limited time of a patient encounter.

Establishing a start-up on an established electronic medical record (EMR) like Athenahealth’s can be a long process. What did that look like from your end?

Rick Newton: More deliberate than people might assume. Enterprise healthcare organizations require technical, product, workflow, and operational scrutiny. We went through several weeks of due diligence with athenaOne’s product team before the work was finalized. For us, that process was important because it tested the core premise of Reveali: observational, non-clinical data analytics become materially more valuable when it can be structured and delivered inside the systems healthcare organizations already rely on. Many companies have described that bridge conceptually. The harder task is making it usable in a real enterprise workflow, and Reveali does that with scale.

Why do you think earlier attempts — including, from what you’ve described, some of your own years ago — didn’t succeed?

Rick Newton: Timing is a major part of it. I worked on an earlier version of this idea more than a decade ago, with much larger partners involved, and the economics and technology were not yet ready. Processing large volumes of unstructured, real-world observations into something timely and clinically digestible was simply too difficult and too expensive. Modern AI combined with Reveali’s intellectual property and know-how about stacking the technology properly changes that equation. It can help transform a continuous stream of observational signals and information into a concise longitudinal picture that a physician or care manager can use in minutes. That shift is important not only clinically, but economically: it creates a path to scale without requiring the same growth in manual review.

What was the sticking point with athenaOne, if there was one?

Tony Roth: The challenge was not whether the underlying information could be meaningful; it was whether it could be made useful at the moment a clinician needs it. A physician is not going to read a stack of raw observational notes during a short visit. The work was in converting those “signals” or observations into an ongoing, monitorable view that the system can surface efficiently. We coined the word “clinicize,” which we define as collecting nonclinical data and verifying it via a medical provider to make it clinically valuable. From an enterprise perspective, that is the difference between data collection and deployable intelligence: the information must be structured, continuously updated, and delivered in a form that fits the existing workflow.

How involved was athenaOne’s team in shaping this process?

Tony Roth: It was collaborative from a regulatory perspective. There were points where members of athenaOne’s support team told us they had not seen their platform capabilities placed into such a streamlined workflow before — using existing capabilities to surface longitudinal analytics rather than a one-time visit or treatment.  What mattered to us was the product dialogue itself: the integration to follow will  shape how information can be surfaced practically from traditional healthcare workflows.  While the Reveali risk stratification engine, evaluation, and scoring algorithms reside on its own EMR security-grade platform for proprietary purposes, athenaOne expedites and facilitates adoption by clinicians around the world.

What’s actually new here, versus repackaged?

Rick Newton: The underlying clinical insight is not new. Geriatric care managers and experienced clinicians have understood for decades that changes in behavior, function, routine, and wellness can precede more obvious clinical deterioration. What is different is the ability to operationalize those observations at scale, organize them longitudinally, and surface the resulting intelligence inside the record a physician already uses. We believe that combination — real-world observation, AI-enabled synthesis, and workflow integration — is where a new category of health-risk-intelligence can emerge. We are still early, and we think the right way to validate that thesis is through measurable outcomes. We have begun onboarding patient trials, and the next phase is about demonstrating utility, repeatability, and value.

What comes next?

Tony Roth: The immediate priority is scale. We are focused on rolling out the model with our EMR service partner, athenaOne: Can it be deployed consistently on a personalized basis across dynamic populations and organizations? Will our data configuration reveal more utilization such waste, fraud and abuse? In parallel, we are continuing conversations around actuarial and risk applications, where longitudinal health-risk intelligence may have relevance for organizations managing reserve cost, utilization, and morbidity risk. That is a separate track we expect to discuss in more depth later. For now, the milestone is clear: move from successful launch to demonstrated enterprise value and scale.

This is sponsored content. Reveali is a paid partner of Aging in America News; the views expressed by Reveali’s founders are their own.