Applied AI · Regulated workflow
Healthcare AI workflow
Connecting external healthcare AI capabilities to a cloud-native workflow platform in NHS and hospital contexts.
Outcome
AI-generated transcription, facts, and clinical documents moved into a traceable workflow for review and downstream action.
Context
Healthcare AI can create useful clinical output, but value appears only when that output reaches the right people and systems through a reliable operational path.
Challenge
Integrate real-time AI output into a regulated workflow while keeping the surrounding clinical process clear, trackable, and operationally dependable.
Approach
Make the system work.
- 01
Lead the engineering team responsible for the healthcare workflow application.
- 02
Integrate live transcription, fact extraction, and generated medical documentation from external AI capabilities.
- 03
Route the resulting documents and actions through the existing workflow platform.
- 04
Use Azure architecture, automated delivery, monitoring, and close stakeholder collaboration to support reliability.
Impact
What changed.
- Turned AI output into usable workflow rather than a disconnected point solution.
- Supported traceable handoffs between clinicians, patients, and clinical systems.
- Reduced friction around documentation in regulated healthcare workflows.
Disciplines
- Healthcare AI
- Azure
- Workflow platforms
- Cloud-native SaaS