Deepgram Migration Deep Dive

Prerequisites

• An inventory of existing audio/transcript flows, data retention/consent obligations, evaluation fixtures, and rollback owner.
• A staging environment with separate credentials and a compatibility/quality acceptance threshold.

Examples

Run the old and new transcription flow against approved non-sensitive fixtures, compare aggregate accuracy/latency/error metrics, and route a small reversible staging canary only after acceptance passes. Roll back immediately on quality, consent, or operational regression; do not bulk-migrate or reprocess customer recordings before the observation window closes.

Current State

!npm list @deepgram/sdk 2>/dev/null | grep deepgram || echo 'Not installed' !npm list @aws-sdk/client-transcribe 2>/dev/null | grep transcribe || echo 'AWS Transcribe SDK not found' !pip show google-cloud-speech 2>/dev/null | grep Version || echo 'Google STT not found'

Overview

Migrate to Deepgram from AWS Transcribe, Google Cloud Speech-to-Text, Azure Cognitive Services, or OpenAI Whisper. Uses an adapter pattern with a unified interface, parallel running for quality validation, percentage-based traffic shifting, and automated rollback.