Draft completion rate
93%
+8% vs pilot week 1Potential adverse events often surface inside routine patient-support interactions, where unstructured notes create missing minimum case facts and slow reviewer handoff. Safety Intake Desk fixes that first mile with guided capture, recoverable incomplete drafts, and a cleaner path to qualified PV review.
Workflow demo
AI-assisted first-mile intake: turn messy source text into a review-ready safety case draft.
Start with unstructured source material. The model drafts a structured intake case, and reviewers confirm low-confidence fields before handoff.
Load a sample run to simulate deterministic extraction.
Case is retained with timestamp, missing fields, and routed to reviewer queue with "follow-up needed" status.
| Case | Patient | Priority | Status | Submitted |
|---|---|---|---|---|
| AE-2026-0431 | PAT-REDACTED-1042 | High | Needs medical review | 10:06 ET |
| AE-2026-0432 | PAT-REDACTED-1098 | Medium | Follow-up requested | 10:21 ET |
| AE-2026-0433 | PAT-REDACTED-0994 | Low | Ready for handoff | 10:40 ET |
Coordinator
Nurse
Reviewer
Packet PKT-AE-2026-0431 is prepared for Safety Operations Inbox.
Queued for secure transfer
93%
+8% vs pilot week 127 min
-11 min week-over-week82%
+6% this week0 cases
stableOpen another workflow view
The workflow stays narrow on purpose: source notes, call transcripts, or emails enter first; a model builds an initial structured draft; reviewers focus on low-confidence fields; and complete, trusted cases exit as handoff-ready packets with visible status and audit context. The heavier rationale, delivery assumptions, and pilot notes live in the appendix.