Teams working with voice data like customer service calls, telehealth sessions, or financial consultations all face a shared challenge: how to leverage these insight-right touchpoints for model training and analysis while still protecting privacy and adhering to compliance requirements.
Tonic Textual’s Synthetic Audio capability unlocks audio for AI development – securely and at scale.
Users can redact large quantities of audio files with a quick SDK call or simply drag-and-drop audio files within the UI to generate privacy-protected transcripts
Demo: Generating privacy-protected transcripts from audio files using Tonic Textual.
Install the Textual Python SDK
Create an SDK client
Specify local file locations to ingest recordings via the Textual SDK
Specify a generator:
Generate transcripts in JSON
Export for downstream use
Want to test it out? We’ve included all of the assets from the video in the playbook so that you can experiment on your own.
Tonic.ai comes ready with out-of-the-box support for a rich library of entity types—so your data is understood from day one. From names, dates, and locations to nuanced healthcare, finance, and developer-specific fields, our proprietary models are designed to recognize the structures and semantics that matter most. Whether you're redacting sensitive information or sanitizing datasets with true-to-life synthetic replacements, these built-in types form the backbone of smarter, safer data workflows.