Multimodal Workflow
Meeting Workflow
A runnable meeting review workflow that turns audio, screen material, images, and documents into a traceable workbench.
Problem
Meeting material often arrives as scattered audio, screen recordings, screenshots, slides, and notes. A useful AI product has to preserve source context and workflow state, not only produce a transcript.
Workflow
- 01Capture or upload audio, screenshots, slides, and video material into one session.
- 02Normalize inputs into source units, run processing steps, and track visible state transitions.
- 03Generate transcript, chapters, action items, and reviewable results.
- 04Expose redacted sharing and download surfaces so outputs can be checked before circulation.
Evidence
Workbench
Home workbench showing the session-oriented operating surface.
Upload and processing
Upload and process steps demonstrate the workflow boundary before model output.
Result review
Result workbench shows generated outputs as reviewable artifacts.
42 validation checks
Backend validation checks grouped into ASR, capture, dedupe, timeline, result API, note style, auth/session, and video ingest categories.
Redacted share page
A safe share-page screenshot demonstrates public-output boundaries.
Boundary
- This is a runnable MVP, not a mature enterprise SaaS.
- The 42 checks are backend validation and acceptance categories, not a full production QA organization.
- Production hardening would still require worker orchestration, audit logs, fixed evaluation reports, and stronger source citation.
Role Mapping
- AI application product: converts messy inputs into a visible workflow.
- Agent workflow / Eval: defines state, validation, failure categories, and human review points.
- AI POC / solution product: demonstrates prototype-to-reviewable-output delivery.