Manifold Health AI announced its public debut during JPM Healthcare Week and the GMT MedTech Symposium, introducing a first-of-its-kind platform that combines a precision-designed blood test with an AI-powered Digital Health Index Twin. The platform is built to translate biological signals into financial risk intelligence for healthcare systems, payers, and employers. The launch was presented by Jerome Scelza, Founder and Chief Executive Officer of Manifold Health AI, who outlined the company’s goal of reshaping how chronic disease risk is identified and managed.
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The idea behind Manifold Health AI emerged from a key insight into the limitations of the at-home diagnostics market. While blood collection technology has advanced significantly, Jerome Scelza explained that devices alone do not scale without a clear and economically aligned use case. He noted that the real challenge has never been collecting blood but rather the lack of financial relevance for prevention within the existing healthcare system. According to Scelza, most people living with chronic disease are not part of cash-pay wellness models, which means the populations driving the highest risk are often overlooked. Manifold Health AI was created to align incentives by showing health plans, employers, and underwriters that frequent and targeted blood testing can reduce risk and improve outcomes.
At the core of the platform is a proprietary blood-based risk assessment designed to identify costly health events before they appear in claims data. Instead of relying on surveys or historical billing information, Manifold Health AI starts with objective biological markers and connects them directly to real financial outcomes. This approach produces a standardized individual risk score, comparable in concept to a credit score, that allows organizations to forecast health risk proactively rather than reactively.
Scelza explained that for decades, healthcare risk models have been built around billing codes created for reimbursement rather than clinical insight. As a result, most forecasting looks backward and does little to support prevention. He said the team asked a fundamental question about what data truly matters at the point of care. The answer, he noted, was bloodwork, which remains the first and most direct tool clinicians use to assess patient health.
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Early findings from a pilot study highlight the scale of unmet need. In a study involving five hundred manufacturing workers in southern Mississippi, Manifold Health AI found that more than eighty percent had at least three biomarkers outside normal ranges, indicating moderate to high risk that had not been previously identified. Scelza said this group reflects the reality of much of the U.S. population and contrasts sharply with typical consumer wellness audiences where results are often normal and insights limited. He emphasized that Manifold Health AI is building for populations that traditional wellness models fail to reach.
The company’s long-term vision is to serve as a bridge between biology and finance by making biological risk economically measurable and actionable. By doing so, Manifold Health AI aims to help preventive care reach people who need it most, not just those who can afford premium wellness services. The platform integrates advanced tools such as next-generation diagnostics, biological age measurement, and continuous risk monitoring to support earlier intervention in chronic disease.
Jerome Scelza is a Johns Hopkins trained biomedical engineer and computer scientist with more than a decade of experience building health technology companies. He previously served as Chief Executive Officer of Drawbridge Health, where he led the development of the first FDA-cleared over-the-counter self-administered blood collection device. As Founder and CEO of Manifold Health AI, he is now focused on connecting biological data with financial risk modeling to expand access to proactive and precision healthcare.
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