Zoom AI Services Scribe
Background reference for Zoom AI Services Scribe across:
- synchronous single-file transcription (
POST /aiservices/scribe/transcribe) - asynchronous batch jobs (
/aiservices/scribe/jobs*) - browser microphone pseudo-streaming via repeated short file uploads
- webhook-driven batch status updates
- Build-platform JWT generation and credential handling
Official docs:
- https://developers.zoom.us/docs/ai-services/
- https://developers.zoom.us/docs/ai-services/scribe/
- https://developers.zoom.us/docs/api/ai-services/
- https://developers.zoom.us/api-hub/ai-services/methods/endpoints.json
- Quickstart sample: https://github.com/zoom/scribe-quickstart/
Routing Guardrail
- If the user needs uploaded or stored media transcribed into text, route here first.
- If the user needs live meeting media without file-based upload/batch jobs, route to ../rtms/SKILL.md.
- If the user needs Zoom REST API inventory for AI Services paths, chain ../rest-api/SKILL.md.
- If the user needs webhook signature patterns or generic HMAC receiver hardening, optionally chain ../webhooks/SKILL.md.
Quick Links
- concepts/auth-and-processing-modes.md
- scenarios/high-level-scenarios.md
- examples/fast-mode-node.md
- examples/batch-webhook-pipeline.md
- references/api-reference.md
- references/environment-variables.md
- references/samples-validation.md
- references/versioning-and-drift.md
- troubleshooting/common-drift-and-breaks.md
- RUNBOOK.md
Core Workflow
- Get Build-platform credentials and generate an HS256 JWT.
- Choose fast mode for one short file or batch mode for stored archives / large sets.
- Submit the transcription request.
- For batch jobs, poll job/file status or receive webhook notifications.
- Persist and post-process transcript JSON.
Hosted Fast-Mode Guardrail
- The formal fast-mode API limits are
100 MBand2 hours, but hosted browser flows can still time out before the upstream response returns. - Current deployed-sample observations:
- ~17.2 MB MP4 completed in about 26s - ~38.6 MB MP4 completed in about 26-37s - ~59.2 MB MP4 completed in about 32-34s on the backend - some ~59.2 MB browser requests still surfaced as frontend 504 while backend logs later showed 200
- Treat frontend
504plus backend200as a browser/edge timeout race, not an automatic transcription failure. - For hosted UIs, prefer an async request/polling wrapper for fast mode instead of holding the browser open for the full upstream response.
- For larger or less predictable media, prefer batch mode even when the file is still within the formal fast-mode size limit.
Browser Microphone Pattern
scribedoes not expose a documented real-time streaming API surface.- If you want a browser microphone experience, use pseudo-streaming:
1. capture microphone audio in short chunks 2. upload each chunk through the async fast-mode wrapper 3. poll for completion 4. append chunk transcripts in sequence
- Recommended starting cadence:
- chunk size: 5 seconds - acceptable range: 5-10 seconds - in-flight chunk requests: 2-3
- This is a practical UI pattern for incremental transcript updates, not a substitute for
rtms. - Treat this as a fallback demo pattern, not the preferred production architecture.
- It adds repeated upload overhead, chunk-boundary drift, browser codec/container variability, and transcript stitching complexity.
- If the user asks for actual live stream ingestion, low-latency continuous media, or server-push media transport, route to ../rtms/SKILL.md instead.
Endpoint Surface
| Mode | Method | Path | Use |
|---|---|---|---|
| Fast | POST | /aiservices/scribe/transcribe | Synchronous transcription for one file |
| Batch | POST | /aiservices/scribe/jobs | Submit asynchronous batch job |
| Batch | GET | /aiservices/scribe/jobs | List jobs |
| Batch | GET | /aiservices/scribe/jobs/{jobId} | Inspect job summary/state |
| Batch | DELETE | /aiservices/scribe/jobs/{jobId} | Cancel queued/processing job |
| Batch | GET | /aiservices/scribe/jobs/{jobId}/files | Inspect per-file results |
High-Level Scenarios
- On-demand clip transcription after a user uploads one recording.
- Batch transcription of stored S3 call archives.
- Webhook-driven ETL pipeline that writes transcripts to your database/search index.
- Re-transcription of Zoom-managed recordings after exporting them to your own storage.
- Offline compliance or QA workflows that need timestamps, channel separation, and speaker hints.
Chaining
- Stored Zoom recordings -> ../rest-api/SKILL.md +
scribe - Webhook verification hardening -> ../webhooks/SKILL.md
- Real-time live transcript/media -> ../rtms/SKILL.md
- Cross-product routing -> ../general/SKILL.md
Operations
- RUNBOOK.md - 5-minute preflight and debugging checklist.