Clinical AI Model Engineering
Develop and evaluate AI capabilities for healthcare-focused use cases.
Illustrative imageryWhat this service involves
Problem discovery, model and data requirements, evaluation planning and implementation under an agreed scope.
Who we work with
Healthcare AI developers, digital health providers and research teams.
Planning a project?
Share the modality, intended use, approximate volume and the type of clinical or technical expertise you need. We can discuss a suitable project scope.
Start a project enquiryAreas of support
Healthcare AI problem and workflow definition
Requirements, quality measures and deliverables are tailored to the agreed project scope.
Data readiness and model evaluation plans
Requirements, quality measures and deliverables are tailored to the agreed project scope.
Engineering, implementation and testing scope
Requirements, quality measures and deliverables are tailored to the agreed project scope.
How a project is scoped
We begin with the intended AI or research application, then agree on data specifications, expertise, review stages, quality criteria and delivery format. Project commitments are defined in a written proposal or agreement.
- Requirements and feasibility discussion
- Data rights, privacy and security considerations
- Annotation, review and acceptance requirements
- Deliverables, pricing and milestones agreed in writing
Enquire about Clinical AI Model Engineering
Use a service enquiry rather than a ShevsHealth product waitlist.
Request a service proposal