Building open infrastructure for healthcare AI.
VersionOne Health develops open-source tools, evaluation frameworks, benchmarks, and developer infrastructure that help healthcare organizations build, deploy, and evaluate AI systems safely and responsibly.
Our mission is to make healthcare AI more transparent, measurable, and trustworthy.
Evaluate healthcare AI systems for safety, reliability, coding accuracy, compliance, and operational performance.
- GitHub: https://github.com/VersionOne-Health/healtheval
- Live Demo: https://healtheval-versionone.streamlit.app
Capabilities
- Clinical AI evaluation
- Medical coding validation
- Failure mode analysis
- Quality benchmarking
- Healthcare-specific test scenarios
- Interactive Streamlit dashboard
Tools and frameworks for evaluating healthcare AI systems before production deployment.
Methods for identifying hallucinations, clinical inaccuracies, unsafe recommendations, and workflow risks.
Evaluation of CPT, ICD-10, HCC, documentation quality, and coding accuracy.
Open healthcare AI benchmarks, reference datasets, and reproducible evaluation methodologies.
Tools supporting transparency, auditability, explainability, and healthcare AI governance.
Reusable components and developer tools for healthcare AI builders.
Whenever possible, our tools, methodologies, and benchmarks are shared publicly.
Healthcare AI should be measurable using transparent and repeatable methods.
Clinical safety and patient outcomes matter more than benchmark scores.
We prioritize tools that solve real-world healthcare problems.
Healthcare AI improves when researchers, clinicians, developers, and operators collaborate openly.
- Healthcare AI startups
- Digital health companies
- Clinical AI researchers
- Healthcare providers
- Health systems
- Medical coding teams
- Revenue cycle teams
- AI engineers and developers
Our initial focus is building evaluation infrastructure for healthcare AI applications, including:
- Clinical reasoning evaluation
- Documentation quality assessment
- Medical coding validation
- Safety testing
- Failure mode detection
- Operational performance benchmarking
We welcome contributions from developers, clinicians, researchers, and healthcare operators.
Ideas for contribution:
- Evaluation scenarios
- Failure mode definitions
- Clinical datasets
- Documentation improvements
- Benchmarks
- Tooling and integrations
Please open an issue or submit a pull request.
🌐 Website: https://versionone.health
📂 GitHub Organization: https://github.com/VersionOne-Health
🚀 HealthEval Demo: https://healtheval-versionone.streamlit.app
Transparent evaluation. Reproducible benchmarks. Open infrastructure.