Six dimensions of healthcare-AI diligence
Clinical or administrative utility
The system should improve a decision, remove work, increase capacity, reduce risk, or protect revenue in a way users can observe.
Workflow integration
Technical accuracy is insufficient if the product creates new screens, alerts, documentation, or handoffs without removing greater friction elsewhere.
Data rights and defensibility
Investors should understand the origin, permitted use, representativeness, portability, and ongoing cost of the data required to train and operate the system.
Validation and monitoring
Healthcare AI needs prospective evidence appropriate to its claim, plus monitoring for drift, bias, safety events, and changes in clinical practice.
Unit economics
Inference, implementation, integration, support, security, and human-review costs must fit inside a credible pricing and gross-margin model.
Enterprise adoption
The real buyer may sit in a clinical service line, IT, compliance, finance, or operations. Successful companies align the value proposition across all necessary stakeholders.
Where M3A focuses
M3A looks for AI systems embedded in high-value healthcare workflows, including surgery, medical imaging, monitoring, administrative operations, musculoskeletal assessment, and behavioral health.