Redact sensitive data for

Train LLMs on your free-text data while ensuring compliance and keeping sensitive information safe with Tonic Textual.
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UI and Python SDK workflows

Redact your free-text files in just a few steps:

1. Upload .txt or .pdf files through the UI or Python SDK.
2. Preview sensitive data detection and configure transformations.
3. Download or fetch your redacted data.
Customize models to detect and redact sensitive data
Example dataset showing transformation and synthesis

Simple redaction or realistic synthesis

Transform sensitive data in your unstructured text into redacted entities or contextually relevant synthetic data. Preserve the realism of your training data and customize the output for bias detection to ensure that your models accurately predict the full breadth of your scenarios.

Custom sensitive data detection

Customize what Tonic Textual detects as sensitive by training our entity recognition model to meet the unique needs of your data. Redact the data that uniquely matters to your organization.
Dataset name example
Try it out in real-time
Paste in your text below or try a provided sample text. Tonic Textual scans for 17 standard data types, but you can add fully-customized data model types to fit your needs.
Start for free with one-click via AWS Marketplace

Fuel your models with Tonic Textual today

Safeguard your most important data while unlocking the power of LLMs.