MediXplain helps healthcare organizations make AI decisions transparent for clinicians, patients, and regulators.
Black-box AI creates clinical risk and slows adoption
Clinicians need evidence, regulators need documentation
Patients deserve explanations they can understand
Model explanations with clear visualizations
Plain-language summaries for all stakeholders
Complete audit trails and governance tooling
Built for hospitals, diagnostic centers, and research institutions.
Three simple steps to bring transparency to your AI workflows
Connect to models and datasets securely, evaluate bias and performance metrics
SHAP/LIME/Captum-based explainers with saliency maps and feature attributions
Clinician-grade and patient-friendly summaries with exportable reports
Bringing transparency to critical healthcare AI applications
X-ray/CT explanations with heatmaps and visual attributions
Medication and treatment reasoning with evidence trails
Plain language summaries patients can understand
Measurable improvements in AI transparency and trust
Reduce time-to-explain
Faster AI decision documentation
Improve clinician trust
Enhanced confidence in AI recommendations
Accelerate compliance
Streamlined regulatory reviews
* Illustrative KPIs; pilot-dependent.
No; we support it with transparent evidence and clear explanations.
Yes, deployment options available for on-premises and cloud environments.
We design with high-risk AI obligations in mind and compliance requirements.