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AI · TRANSCRIPTION · PIPELINE · 2026
Fractional AI & Dev Tech Lead · 2026

Cadence Translate — Transcription Pipeline & MegaEditor

Expert-call transcription for the investment world: an ASR and LLM pipeline feeding a word-level review editor. Audio in, human-verified multilingual transcripts out.

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Word-level
Editing + audio sync
ASR + LLM
Processing pipeline
5 stages
Review workflow
3 apps
API · Admin · Editor
✦ Full pipeline: ASR → LLM → human QA✦ Word-level audio-sync editor✦ DDD FastAPI platform
THE HARD PART

“Making AI transcription trustworthy. The async ASR and LLM pipeline feeds a word-level editor with audio sync, versioned drafts, and optimistic locking, so reviewers spend their time correcting the model instead of fighting the tool.”

Cadence Translate — Transcription Pipeline & MegaEditor — 1

Cadence Translate turns expert calls and multilingual audio into transcripts a hedge fund can actually rely on. The model does the fast first pass; people make it trustworthy. The heart of that human stage is MegaEditor, the piece I enjoyed most: a full-stack transcription editor (FastAPI + React 19) with word-level editing on per-word timestamps, audio that follows the text as you click, speaker assignment, segment review, undo/redo, drafts that save themselves, version snapshots, and optimistic locking so two editors can't silently overwrite each other.

Cadence Translate — Transcription Pipeline & MegaEditor — 2

Editing is only half the human stage. Transcripts move through a RECEIVED, EDITING, REVIEWING, APPROVED, COMPLETED workflow with separate roles for editors, reviewers, and internal QA, and review mode adds an annotations panel so a reviewer can mark up the transcript itself before anything ships.

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An order comes in through the API and the audio runs through ASR and LLM post-processing for grammar and entity recognition, step by step through a 41-step pipeline that operations can actually see: every transcript shows its current step, its status, its turnaround target and how far it is from due, filterable across the whole book of work.

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When a step fails, the transcript page says so in plain terms: the exact error, what the step was supposed to do, how to retry safely, and when a retry is the wrong move. Diagnosing a stuck job takes a minute of reading instead of a dig through the logs.

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Around the pipeline sits the operations surface: orders tracked from pending through in progress to completed, per account and per user, so the team runs the whole book of business from one screen instead of a spreadsheet.

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The core platform is a FastAPI monolith organized by domain: orders, freelancer assignment, webhook callbacks, and delivery each live in their own module, with PostgreSQL, Redis, and Dramatiq workers running the async pipeline stages, and a Next.js 15 dashboard on top for the operations team. Cadence itself is a language services provider to the global business and investment community, which is why the transcripts have to be right.

STACK
PythonFastAPIPostgreSQLRedisDramatiqNext.jsReact 19TypeScriptSQLAlchemyLLMsASRDocker