Set a clear research task
Define the source material, question and desired output. Keep patient information and sensitive records out of public inquiries.
Assisted research
Move research forward.
Keep judgment accountable.
Explore a workflow where automation can help prepare and structure material while people remain responsible for review and publication.
Review generated material
Treat machine-generated material as work to assess. Check sources, limitations and transformations before accepting a result.
Confirm operating boundaries
Discuss approved model use, data handling and reviewer responsibilities in your evaluation. No clinical accuracy or autonomous care decision is promised.
Make the model tangible.
Inspect a fictional record from source through review and publication. Download a small JSON fixture and test it locally.
Explore the sample ↗Confirm your requirements.
Evaluation scope, supported interfaces, source rights and service commitments depend on your proposed use. Discuss them before sending any real data.
Read evaluation boundaries ↗Start with your workflow