Companies building healthcare AI today are undertaking some of the most challenging and ambitious work in the technology sector. The pace of innovation is extraordinary— what seemed impossible just months ago is now becoming possible as teams push the boundaries of what AI can do in clinical settings. These pioneers are truly at the cutting edge, combining complex machine learning, biomedical knowledge, and clinical workflows in ways never before attempted.

Yet the cutting edge needs to be handled with care. When you're breaking new ground, there is uncertainty everywhere and perfection is the not the top priority yet. The hard truth about frontier technologies is that they're rarely polished on arrival— they need iteration, refinement, and wisdom gained in testing and application. In most industries, this evolution is perfectly normal.

Healthcare is different. Here, the margin for error is vanishingly small, and the consequences of mistakes can be profound. The path to widespread adoption doesn't run through "good enough" or "mostly accurate" – it demands reliability that is close to perfection. Only AI systems that consistently demonstrate exceptional accuracy will earn the trust needed to unlock their full potential in improving patient outcomes, expanding access to care, and making healthcare more efficient and effective.

In this era where AI promises to transform healthcare, we still need to take a hard look at the outcomes. That's why we're introducing Reality.check™— an initiative bringing together healthcare AI companies committed to accuracy above all.

The accuracy gap in healthcare AI

When lives are at stake, "good enough" simply isn't. This truth becomes startlingly clear when we examine the results from HealthBench, one of the latest measurement frameworks comparing the performance of leading foundation models on healthcare tasks.

The findings are illuminating— and concerning. Even OpenAI's newest model, o3, considered one of the most advanced general-purpose models, achieved only a 60% accuracy score on specialized healthcare challenges. Other industry leaders like Grok and Gemini scored just 54% and 52% respectively. In a domain where errors can lead to misdiagnosis, inappropriate treatment recommendations, or worse, these numbers reveal the significant gap between current capabilities and the near-perfect accuracy healthcare demands.

The dual path to excellence

What Reality.check™ recognizes— and what leading AI companies across industries have discovered— is that algorithmic improvements alone aren't enough. The path to truly reliable AI lies in combining cutting-edge technology with human expertise in structured, scalable ways.

We've seen this approach transform AI applications in other high-stakes domains. In legal tech, models trained with attorney oversight have dramatically reduced error rates in contract analysis and case research. Financial services firms have achieved similar breakthroughs by pairing quantitative models with expert traders and analysts who refine outputs and identify edge cases. Manufacturing companies have likewise seen quality control systems reach new levels of reliability through the integration of engineer-guided training and validation workflows.

Each success story follows the same pattern: experts working in tandem with algorithms, not just to catch mistakes but to teach the systems how experts think.

The Reality.check™ commitment

When an AI company joins Reality.check™, they're making a public commitment to accuracy and safety that goes beyond platitudes. They're embracing a comprehensive approach that combines:

• Advanced algorithmic development focused on reducing hallucination and error rates

• Integration of doctors and other healthcare experts throughout the AI lifecycle

• Rigorous evaluation against gold-standard benchmarks

• Continuous improvement based on real-world performance

• Transparency about capabilities and limitations

For healthcare organizations evaluating AI solutions, the Reality.check™ designation provides immediate assurance that a vendor prioritizes clinical quality and patient safety. When potential clients ask, "How do you ensure accuracy and clinical quality?"— Reality.check™ members can point to a comprehensive framework built on the proven combination of human expertise and technological innovation.

Building the future of healthcare AI, responsibly

The gap revealed by HealthBench doesn't diminish AI's potential to transform healthcare— it simply highlights the work still to be done and the approach needed to get there. The most successful healthcare AI companies will be those that recognize accuracy isn't just a technical challenge but a clinical one, requiring deep integration with medical expertise.

Reality.check™ represents a collective commitment to this vision: AI systems that doctors can trust because doctors helped build them. Systems that reach the level of reliability healthcare demands because they're developed with the understanding that in medicine, excellence isn't aspirational— it's essential.

For AI companies ready to prioritize accuracy above all, Reality.check™ isn't just a standard to meet— it's a movement to join. Together, we're building AI that healthcare can truly rely on, one verified prediction at a time.