Audio is everywhere - meetings, support calls, interviews, voice notes. But audio on its own is hard to work with. Flowrunner’s Speech-toText block converts recordings into accurate, structured text you can search, analyze, and feed into any automation.

What It Does

The block uses OpenAI’s advanced Whisper models to transcribe audio into text. It supports over 90 languages, handles background noise and accents, and works with common formats like MP3, WAV, and M4A.

Upload a file or capture a recording, and the block delivers clean, usable text as the output.

Why It’s Powerful

Text is compact, searchable, and easy to process with other AI tools. By turning voice into text:

• You make conversations indexable for search or storage.
  
• You create data points that can feed into CRM systems, reports, or analytics.
  
• You free teams from the overhead of manual transcription.
  

It’s the fastest way to unlock the value hidden in your audio files.

Real-World Use Cases

• Customer Support → Transcribe calls into searchable records and push key points into your CRM.
  
• Meetings → Turn recordings into structured notes and action items.
  
• Content → Auto-generate transcripts for podcasts, webinars, or training videos.
  
• Compliance → Maintain searchable logs of regulated conversations.
  

Why It Matters

With Speech-to-Text, Flowrunner makes audio a first-class citizen in your workflows.
Instead of audio being a dead end, it becomes structured data you can route, analyze, and act on - all automatically.

The Takeaway

Flowrunner’s Speech-toText block is a simple but powerful control that converts audio into the format automation works best with; text.
👉 If your workflows touch audio, make sure they can listen.

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