Happy Scribe integrations and automation

Podcast producers, researchers and video teams use Happy Scribe to turn recordings into transcripts and subtitles, then spend time moving files in and text out. The API removes those steps, but its shape is asynchronous, which shapes every workflow. You do not send a file and get text back in one call. For a local file you first ask for a signed upload URL, upload the media to it, and then create a transcription (or an order) that points at that uploaded file or at a public media URL. Processing takes minutes, and the job moves through states until it reaches automatic_done for machine transcripts.

Getting text out is a second asynchronous step. You create an export for one or more transcriptions in a chosen format, such as txt, docx, pdf or a subtitle format, with options like speaker labels or comments where the format supports them, then fetch the export until it is ready and download it from the link it returns. A workflow therefore needs either a later check or a webhook. Orders accept a webhook_url, and Happy Scribe calls it every time the order changes state, which avoids polling.

Orders also let you choose the service: auto for machine transcription, pro for transcripts or subtitles made by human professionals, and alignment to match an existing script to the media. Pro work costs more and takes longer, and not every language offers it; the language table in the docs marks which codes support human service. Language is given as a locale code such as en-GB or es-MX, and picking the right variant improves results.

Authentication is a Bearer API key from your Happy Scribe account page. The documented rate limit applies per user on the transcription creation endpoint: 200 requests an hour by default, with a 429 response carrying retry_in_seconds when exceeded. Bulk back-catalogue jobs should be spaced out or queued. Transcripts belong to an organization and can be filed into folders by id, so decide in advance where automated jobs land.