Three ways to work together, scoped around a measurable result. Most clients start with an assessment and continue from there.
A short, fixed-scope engagement that maps your data landscape, separates what AI can realistically do now from what it cannot, and ends with a roadmap you can budget against. Includes independent evaluation of AI vendors and support on AI-specific RFPs.
Implementation that reaches production. We connect the systems, build the models and dashboards, and stay through delivery, because the gap between a working prototype and a deployed workflow is where most healthcare AI dies.
Independent validation and governance for AI you have built or purchased: performance testing against defined thresholds, bias and subgroup analysis, audit trails, and monitoring that keeps running after go-live.
A separate practice for research teams: study design and analysis plans, genomic and clinical data pipelines, and publication-ready statistics.
Most clients begin with a short discovery engagement. We map your data landscape and hand you a prioritized roadmap.
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