Tonic.ai announces Unstructured Data Catalog for Tonic Textual

New capability gives teams centralized visibility, intelligent search, and deeper insights into sensitive unstructured data.

SAN FRANCISCO — January 29, 2026 — Tonic.ai today announced the general availability of the Unstructured Data Catalog for Tonic Textual, a new capability designed to help organizations understand, discover, and govern sensitive information across unstructured text data at scale.

As enterprises increasingly rely on unstructured data to power AI and analytics initiatives, gaining visibility into where sensitive information exists — and how it is used — has become a critical challenge. The Unstructured Data Catalog addresses this by centralizing text data across thousands of documents into a searchable, queryable system of record.

“Most organizations are sitting on thousands or millions of documents they cannot use simply because they do not know what is inside them. The unstructured data catalog changes that by giving teams clear, searchable visibility into their text data so they can understand risk, identify value, and finally put that data to work for AI.”

Adam Kamor Co-founder and Head of Engineering

Textual detects sensitive entities in unstructured text and replaces them with realistic synthetic alternatives or redacts them outright, preserving essential context while making data safe to use for AI model training. The updated Datasets UI introduces a centralized data catalog that organizes content by entity type, file, detection confidence, applied transformations, and context, enabling teams to search millions of words in seconds and quickly identify AI-ready data.

In addition, the catalog introduces an LLM-powered intelligent search assistant that allows users to ask natural-language questions about their datasets, such as how frequently certain entities appear, how data is being transformed, or which documents contain specific attributes. This enables teams to quickly surface insights and export relevant data for downstream use without writing queries or scanning documents.

The Unstructured Data Catalog supports a wide range of use cases, including:

• Selecting and validating privacy-safe data for AI and machine learning development
  
• Providing engineering leaders with visibility into unstructured data assets and risks
  
• Supporting compliance, legal, and risk management through discovery and auditability
  
• Enabling enterprise search and large-scale knowledge discovery
  

By making sensitive data discoverable and auditable, the Unstructured Data Catalog helps organizations confidently operationalize unstructured text while strengthening governance and compliance.

These new capabilities are available now to all users of Tonic Textual.

For more information, visit tonic.ai or request a demo.