Case study
AI-powered clinical intelligence, not just OCR
Traceable extraction from clinical packets with reviewer queues, citations, and alerts.
Snapshot
- Inputs: Clinical packets (PDFs)
- Outputs: Structured fields + alerts
- Controls: Review gates + citations
Secure intake portal with reviewer queues and monitoring.
Problem
Document-heavy intake delayed clinical decisions
Teams needed accurate structured data from clinical packets without manual rekeying or missed signals.
Workflow
Upload → extract → review → alert
Packets uploaded, fields extracted, reviewer queues created, and alerts triggered on predefined conditions.
Implementation
Controls and build details
Governance was wired into the first iteration so reviewers and auditors could see lineage immediately.
1
Step 1
Ingest
Documents uploaded and normalized via secure intake portal
2
Step 2
Extract
Structured fields with confidence and source pointers
3
Step 3
Review
Review queues for uncertain or high-risk extractions
4
Step 4
Alert
Alerts when clinical signals fire
Governance controls shipped
Traceability and human approvals included before expansion.
- Extracted fields tied back to exact source pages with citations.
- Review thresholds and escalation paths for uncertain outputs.
- Monitoring for extraction drift and edge cases with alerts.
Product views
Reviewer-ready intake view
Intake, extraction, and traceability surfaced in a single workflow.
Unified intake view with reviewer queues and document context.
Before / after
What changed for reviewers
Manual copy-paste replaced by reviewer-ready experiences with built-in lineage.
Before
- Manual rekeying from PDFs into systems of record.
- Spotty audit trails when reviewers made changes.
- Slow detection of critical signals across packets.
After
- Structured fields with citations to each source page.
- Review queues with approval notes captured in the audit log.
- Alerts when medication changes or emergency indicators appear.
Outcomes
Impact observed
Measured signals kept stakeholders confident after launch.
Shorter time from document arrival to reviewer-approved structured data.
Reduced human error from manual copy and re-entry.
Earlier alerts on high-risk changes and urgent situations.