AI Data Contracts
Context, model, output schema, provenance, and exclusions are bound before inference.
AI and automation
AI-assisted clinical review with human oversight built in.
Clinistack uses AI to classify documents, read their metadata, spot likely duplicates, and suggest medical coding terms inside controlled workflows. Clinical teams review the output, approve the action, and keep the evidence with the record. AI ships switched off and is enabled per tenant under a data processing agreement, never by default.
Input control
AI should know its lane before it runs.
The useful question is not whether AI exists. It is what data it can see, what output it can produce, what it must exclude, and what proof remains after review.
Model and provenance
Each run records the model the provider reported serving, source context, expected schema, and evidence references used for review.
Excluded data and fallback
Fallback stays available when AI is unavailable, inappropriate, or below the bar for the regulated workflow.
Review
The reviewer owns the regulated decision.
AI output lands as a retained suggestion with status, rationale, confidence, evidence references, and reviewer disposition. The reviewer decision is the regulated record-update event.
Suggested classifications
Document classification, document metadata, likely duplicates, and medical coding terms can be proposed for review.
Accept, edit, or reject
Reviewers get source citations, confidence, and the cited passage before the record changes.
Reviewer decision
The accepted reviewer action, not the model output alone, becomes the regulated write event.
Autonomous actions
Autonomous writes require a higher bar.
Mode 3 is not a shortcut. It requires higher-severity audit, Validated Model Roster approval, explainability, fallback, and CSA high-risk assurance before regulated writes are allowed. No shipped Clinistack workflow enables it: every AI Data Contract in the product refuses autonomous writes today.
Mode 3 gate
Autonomous writes would require approved model roster scope, confidence controls, explainability, and release evidence.
AI provenance
Contract id, mode, model, input provenance, reviewer disposition, and audit event stay reviewable on the document the AI acted on.
No blocked regulated workflow
AI unavailability routes to manual review rather than stopping required clinical work.
First rollout
Bring the study question your team keeps rebuilding.
We will review the product path, system context, owners, evidence, and rollout approach that fit the trial work in front of you.