scribe

Zoom AI Services Scribe

Background reference for Zoom AI Services Scribe across:

Official docs:

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

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 MB and 2 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 504 plus backend 200 as 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

scribe does not expose a documented real-time streaming API surface.
If you want a browser microphone experience, use pseudo-streaming:
capture microphone audio in short chunks
upload each chunk through the async fast-mode wrapper
poll for completion
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

Operations

Source Transparency