Cardiac AI: De-Risking Investments in Value-Based Care

The slow, uneven shift to value-based care is a mess, but it’s also creating some very specific opportunities. In this new world, platforms that can actually manage risk and prove their ROI are the ones that will win. Under the old model, an avoidable cardiac admission was a profit center. Now, it’s a huge liability for a health system. For investors, the only thing that matters is figuring out which AI platforms can make that liability go away and show clear financial results.

The Imperative of Outcomes Data in Value-Based Care AI

The move from fee-for-service to value-based care (VBC) is completely changing the money side of healthcare. Payers, especially the Centers for Medicare & Medicaid Services (CMS), are pushing hard to get providers to deliver better patient outcomes for less money. A huge piece of this is cutting down on avoidable hospital readmissions, particularly for expensive problems like heart conditions. CMS isn’t messing around. Through its Hospital Readmissions Reduction Program (HRRP), it hits hospitals with serious penalties for having too many readmissions. The FY 2026 HRRP performance period ran from July 1, 2021, to June 30, 2024, with payment cuts kicking in on October 1, 2025. Starting in FY 2027, the program gets even bigger, expanding to include Medicare Advantage (MA) patients, not just traditional Medicare. This financial pressure makes health systems desperate for AI solutions that can find at-risk patients and stop bad things from happening. But for an AI platform to get a real VBC contract, it needs to do more than show off its technology. It must provide solid, peer-reviewed outcomes data that spells out exactly how the platform cuts the total cost of care, improves patient health, and reduces those provider penalties. Without that proof, these platforms are just expensive toys, not essential tools for succeeding in VBC.

Hello Heart: A Benchmark for Outcomes-Based AI Health

Hello Heart is a prime example of a company that actually demonstrates tangible, peer-reviewed results that directly create VBC value. Their platform, which focuses on managing hypertension and cardiovascular disease, shows exactly how AI can produce real health and financial improvements, like lower costs and better patient outcomes. While lots of AI companies talk about predictive analytics but can’t show any verifiable impact, Hello Heart has been consistently publishing hard numbers on their effectiveness. Recent studies from August 2026 and May 2026 show they’ve achieved significant cuts in healthcare costs and hospital use for users with heart failure, and they’re even helping reduce socioeconomic gaps in cardiovascular care. Hello Heart has raised $139.3 million total over 6 funding rounds, with its last round being a $70 million Series D in May 2022. Their method isn’t just an algorithm. They combine AI-driven coaching, remote monitoring, and give users information they can actually act on. The key differentiator is the rigorous, peer-reviewed proof showing lower blood pressure, better medication adherence, and a real decrease in cardiovascular events. These aren’t just anecdotes. The figures come from huge datasets and are validated through clinical studies, building the trust needed for VBC adoption. This focus on real-world evidence (RWE) from EHRs, registries, and claims data is exactly what payers and providers need to see when they’re evaluating AI vendors for VBC contracts. Their ability to deliver a clear ROI by preventing avoidable cardiac events makes them an easy choice for any health system operating in this new reality.

AI Platforms Targeting Avoidable Cardiac Events: A Field Analysis

A few AI platforms are trying to get in on reducing avoidable cardiac events, but they’re coming at it from different angles and have wildly different levels of proof that they actually work.

Tempus AI: Using Longitudinal Data for Predictive Insights

Tempus AI, which went public on June 14, 2024, and trades on Nasdaq as “TEM”, is all about aggregating and analyzing massive amounts of patient data over time. Their strength is their huge “data moat”, a proprietary dataset that feeds their predictive algorithms. As of 2026, Tempus has about 38 million research records, including long-term follow-up results, and over 7 billion clinical notes. By pulling together clinical, molecular, and imaging data, Tempus AI tries to spot patients at high risk for cardiac events long before they happen. Their algorithms might flag subtle patterns in a patient’s history that signal an impending heart attack which allows for much earlier intervention. For example, by looking at a patient’s entire health record, Tempus AI could spot a dangerous mix of genetic markers and lifestyle factors that signal a high risk for a stroke. This aligns perfectly with VBC incentives by enabling proactive care that could prevent a costly hospitalization. The data library is huge, no doubt, but for any VC writing a check, the only thing that matters is a peer-reviewed paper that draws a straight line from their prediction to a lower number of cardiac readmissions. (On a related note, Tempus AI also got FDA approval for its tumor-only xT CDx assay, making it the first lab to hold that approval for both tumor-only and tumor-normal genomic profiling, so they clearly know how to handle regulators.)

Viz.ai: Real-Time Decision Support for Acute Care Pathways

Viz.ai’s game is real-time clinical decision support, particularly for stroke and other acute cerebrovascular conditions. Their AI platform looks at medical images (like CT scans), identifies critical findings, and automatically alerts the right care teams, which dramatically cuts down the time to treatment. While stroke has been their main area, the tech and strategy are highly relevant for preventing a secondary cardiac event or just managing an acute cardiac crisis more efficiently. Viz.ai has impressive clinical adoption, with its platform running in 2,000 hospitals across the U.S. as of April 2026. The company has raised $289.25 million across 10 rounds, including a $100 million Series D in April 2022 that valued the company at $1.2 billion. The financial logic is simple: faster, more accurate diagnosis in an acute setting means fewer complications and better recovery, which prevents subsequent events and lowers the total cost of care. Investors need to be asking for published data on how this faster pathway translates into fewer readmissions for cardiac-related problems.

Hippocratic AI: The Role of Conversational AI in Patient Engagement

Hippocratic AI, a safety-focused LLM, attacks the problem from another direction: automated patient outreach. It’s not diagnosing acute events, but it’s tackling the root cause of many avoidable cardiac hospitalizations, poor medication adherence, missed follow-up care, and patients not recognizing early symptoms. Hippocratic AI’s conversational agents can engage patients to give reminders, answer basic questions, and tell them to seek medical help when they need it. This kind of proactive, personalized contact can be a big deal in managing chronic cardiac conditions and stopping them from escalating into an emergency. An AI assistant could, for instance, remind a heart failure patient to weigh themselves daily and report sudden fluid retention, potentially heading off an ED visit. They’ve raised a lot of money: $404 million in total, with a $141 million Series B in January 2025 at a $1.64 billion valuation and a $126 million Series C in November 2025 at a $3.5 billion valuation, the latter led by Avenir Growth Capital and CapitalG. The goal is to improve population health, take some of the burden off clinical staff, and make sure patients stick to their care plans. The test for Hippocratic, like other platforms in this vein, will be to show with large-scale data that all this patient engagement actually results in fewer avoidable cardiac events and lower costs.

The Investor’s Lens: De-risking and ROI in Cardiac AI

For investors and VCs sizing up the cardiac AI field, the focus has to be on platforms that deliver a clear return on investment by fixing financial problems within the VBC framework. This means looking past the tech specs and scrutinizing the quality and quantity of peer-reviewed outcomes data. Platforms like Hello Heart are setting the standard with concrete evidence of reduced cardiac events and costs. For a company like Tempus AI, the value is its data moat and predictive engine, but those predictions need rigorous validation to prove they stop real-world events. Viz.ai’s success in acute care provides a model for efficiency and better outcomes, and if they can expand that into broader cardiac applications, the VBC benefits could be enormous. Hippocratic AI’s work shows just how important patient engagement is for keeping people out of the hospital. The best investment in this space will be a company with a strong data moat and powerful AI, but it also needs a clear path to FDA clearance (e.g., 510(k) or De Novo classification) and, most of all, demonstrable real-world evidence (RWE) of its impact on reducing cardiac events and healthcare costs. The ability to get CPT codes for reimbursement also significantly de-risks the whole commercial plan AMA CPT Code guidelines for AI. VCs should fund the platforms that directly mitigate CMS readmission penalties and lower the total cost of care, because those are the companies built to scale in a value-based future. This analysis is based on digging through CMS policy documents and large-scale health economics datasets to see how AI platforms can identify at-risk patients before an acute event happens, which is the very definition of aligning with VBC incentives.