What This Is
We connect your business systems to Deepgram’s speech-to-text API so that audio and video content is transcribed automatically. Meeting recordings become searchable text, customer calls generate summaries, and voice notes turn into structured data without manual transcription. The integration handles audio file processing, real-time streaming transcription, speaker diarisation, and output formatting.
This is not a transcription service you log into. We build Deepgram into your application so transcription happens as part of your workflow. A project management tool might automatically transcribe client call recordings, extract action items using AI, and attach them to the relevant project. A training platform might transcribe video content and generate searchable captions. The transcription is a processing step inside a larger system, not a standalone task.
A concrete example: a sales team records discovery calls, uploads them to the CRM, and the system automatically transcribes the audio via Deepgram, extracts key topics and next steps using OpenAI, and attaches the structured summary to the deal record. Nobody listens to the recording or takes manual notes.
When You Need This
Deepgram integration is the right choice when your application needs to convert audio to text as part of an automated workflow. Common triggers:
- You have meeting or call recordings that need to be transcribed and made searchable
- You want real-time transcription: live captions for webinars, meetings, or customer support calls
- You need to extract structured data from audio, combining transcription with AI analysis to pull out action items, topics, or sentiment
- You are paying for manual transcription services and want to automate the process at lower cost and higher speed
How We Work
Deepgram integration starts with defining the audio sources, output format, and downstream processing: where recordings come from, what the transcription should look like, and what happens with the text after transcription. This determines whether we use batch processing (pre-recorded files) or streaming (real-time audio).
We build the integration as a processing pipeline inside your application. Audio files are submitted to Deepgram’s API via queue jobs with configurable model selection (Nova-2 for accuracy, Base for speed), language detection, and speaker diarisation. The transcription result is parsed, formatted, and stored in your database, ready for search indexing, AI analysis, or display.
For real-time use cases, we connect to Deepgram’s WebSocket streaming API with proper connection management, reconnection logic, and partial result handling. Live transcriptions are pushed to your frontend via WebSockets (Pusher or native) so users see text appearing as speech occurs.
What You Get
- Batch transcription: pre-recorded audio files processed asynchronously with results stored in your application
- Real-time streaming: live audio transcribed with sub-second latency via WebSocket connection
- Speaker diarisation: multi-speaker identification so transcripts show who said what
- Language detection for automatic identification of multilingual audio content
- Structured output with timestamps, speaker labels, confidence scores, and paragraph formatting
- Downstream integration feeding transcription output into AI analysis, search indexing, or content generation pipelines
Technologies We Use
- Deepgram API: Nova-2 and Base models, pre-recorded and live streaming endpoints, with diarisation and punctuation features
- Laravel: queue jobs for batch processing, WebSocket client management for streaming, and storage of transcription results
- PostgreSQL: transcript storage with full-text search indexing for content discovery
- Redis: job queuing and WebSocket connection state management
Related Systems
Deepgram integration is a processing layer inside content and communication systems. It works inside a CRM that transcribes sales calls, a content management system that generates text from video content, or a training platform that creates searchable transcripts of educational material. For a broader view of our speech and audio work, see the ElevenLabs API Integration page. This capability sits within our AI Development practice and the wider API integrations offering.
Talk to Us About Audio Transcription
If you have audio content that needs to become searchable, analysable text, get in touch and we will design the transcription pipeline.
