Transcribe

What is Transcribe?

Cohere’s Transcribe converts business audio into precise text for search, analytics, and automation, with structured outputs for RAG pipelines.

Accurate speech recognition with emphasis on low word error rate to improve trust in transcript output.
Searchable audio at scale by converting recordings into transcripts that can be indexed and retrieved.
Support for structured outputs in RAG pipelines to help connect transcripts to context-aware responses.
Meeting intelligence capabilities for generating transcripts from call recordings, meetings, and training materials to support audit and analysis.
Voice-powered automations that turn spoken input into actionable signals for workflows, system integrations, and AI agent behavior.
Optimized throughput for efficient model serving in production workflows.
Private deployment options via open weights and small GPU requirements to process sensitive audio locally, compliantly, or in edge environments.
Multilingual support with performance in 14 languages.

Prepare your business audio recordings (for example, calls, meetings, or training content) for transcription.
Run Transcribe to generate precise text transcripts from the audio.
Use the resulting transcripts as searchable text (for knowledge retrieval) or as structured inputs into RAG pipelines.
For voice automation, feed spoken-derived signals from transcripts into your existing workflow, system integrations, or AI agent logic.

Customer support and sales call analysis: Transcribe call recordings into text for review, audit, and analysis.
Internal knowledge search: Convert recorded meetings and training materials into transcripts so employees can search and retrieve relevant information.
RAG-based assistants for business content: Embed structured transcript outputs into RAG pipelines to support grounded, context-aware responses.
Compliance or audit workflows: Produce transcripts of meetings and training materials to document spoken content for later examination.
Production workflow automation: Use voice-to-text transcripts to generate actionable signals that drive integrations and AI agent behavior.

How many languages does Transcribe support? Transcribe supports 14 languages.
Can Transcribe be deployed privately? The page states that Transcribe can be deployed privately, using open weights and small GPU requirements, to process sensitive audio locally, compliantly, or in edge environments.
What kinds of audio does Transcribe target? It’s positioned for business audio data such as calls, meetings, and training materials.
What outputs does Transcribe provide for downstream systems? It converts audio into precise transcripts and supports structured outputs that can be used in RAG pipelines and voice-powered automation workflows.
What performance characteristics are mentioned? The page highlights low word error rate and enhanced throughput optimized for efficient model serving in production.

General-purpose speech-to-text (ASR) models: Alternatives include other ASR systems used to convert audio to text. They may differ in multilingual performance, word-error-rate focus, and how easily transcripts integrate into enterprise pipelines.
Cloud transcription services for enterprise: Hosted transcription APIs can simplify deployment, but may not match Transcribe’s emphasis on private processing with open weights and local/edge deployment.
Meeting transcription and intelligence platforms: Tools focused specifically on meetings and calls may offer additional collaboration features. They can differ in how they expose transcripts for RAG/automation compared with a developer-oriented transcription workflow.
RAG-focused knowledge ingestion tooling: Some solutions emphasize indexing and retrieval of business content rather than transcription itself. They may require pairing with an external transcription step to convert audio into usable text.