I recently shipped HiTranscript, a web app that turns public video URLs and local media uploads into searchable transcripts and subtitle files.
The transcription model was not the hardest part.
The hard part was building a pipeline that stays correct when uploads are large, requests are retried, callbacks arrive twice, a batch partially fails, or a deployment needs to be rolled back.
This post covers the architecture patterns that made the system more reliable: explicit job states, durable media handoffs, idempotent callbacks, item-level batch tracking, and a single normalized timeline for every output format.
The architecture at a glance
