scribe

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 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 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.