Improved generation performance for text, HTML, and JSON files that have non-standard date formats.
The Tonic MCP server now supports the ability to list and redact dataset files. The tools include options to configure the redaction, such as setting the entity type handling options, allow and block lists of specific values, and settings for specific file types.
Form label mapping - In a form label mapping, you map labels in uploaded PDF forms to entity types. For example, you might map the label Government ID to the SSN entity type. After you set up a mapping, you can attach it to datasets. When Textual detects a mapped form label in a dataset PDF file, it identifies the corresponding value as the mapped entity type.
After a file is rescanned, the entity details popup panels on PDF file previews now correctly display the current original value.
Added support for detecting sensitive values in PDF files that contain Mandarin Chinese (Simplified Chinese).
Added LLM-based sensitivity identification and language-preserving synthesis for typed and scanned PDFs that contain Hong Kong Traditional Chinese, including documents that contain a mix of Chinese and English. Requires that an LLM and Azure Document Intelligence are configured.
Added sensitivity detection and value synthesis for PDF files that contain content in Cantonese.
Fixed blank XFA form values in PDF previews and downloads.
Fixed PDF dataset file previews so that numeric option labels next to form checkboxes are no longer misclassified as phone numbers or displayed with overlapping redaction boxes.
Fixed an issue where, after a custom entity type was enabled or disabled for a dataset, the Scan files to apply changes banner did not display until the page was refreshed. The banner now appears immediately.
Improved the dataset file preview for large text files. Previews now load in small character-based pages with infinite scrolling. This allows large .txt files, including single-line files, to open quickly instead of failing to load.
Added support for Azure when using OpenAI provider.
Fixed an issue that occasionally blocked users from reviewing test files for a model-based entity type.
Using color to identify the entity type handling option - In the dataset file previews for text files only, Textual now highlights detected entities based on the entity type handling option:
Purple for redacted values
Blue for synthesized values
Gray for ignored values
The legend in the file toolbar identifies the colors. From the legend, you can show or hide the highlighting for entity values for each handling type. You can still click the values to change the handling option. Textual remembers these settings across files and sessions.
Confidence score thresholds for custom entity types - For each custom entity type in a dataset, you can now set a minimum detection confidence score. On the dataset details, the new Confidence Thresholds tab displays the distribution of confidence scores for each custom entity type. It includes a slider to select the cutoff. Textual ignores detections that score below the threshold. Those values are not redacted or synthesized. The change is applied immediately and does not require a file rescan. In the file preview and entity catalog, ignored detections remain visible, but are marked as Ignored.
On a dataset's Files page, you can now upload files by dragging and dropping them anywhere on the page. This works both for new datasets and for datasets that already contain files.
Fixed an issue where individual signature detections could not be ignored in PDF previews and downloaded files.
Improved support for synthesizing times.
Fixed an issue where when you added a manual redaction to a dataset file, the Entity Type dropdown only listed built-in entity types. You can now also select any custom entity type that is activated for the dataset.
The Request Auditor now supports Redact API requests for JSON and XML.
Users are now automatically signed out after a configurable period of inactivity.
Textual now provides initial support for an MCP server on both Textual Cloud and self hosted instance. This initial version of the MCP server supports creating datasets and uploading files.
Improved entity detection for Hebrew language
Fixed an issue where an incorrect permission check blocked authorized users from viewing the entity types page.
Updated OpenAPI and transformers dependencies to remediate known vulnerabilities.
Request Auditor - The new Request auditor allows you to review the quality of the entity detection in redaction requests to the Python SDK or REST API. It uses an LLM to detect entities in sample subset of the requests and then compares the LLM results to the original detection results. You then review requests that score at or below a configured threshold to see what was missed in the original detection. Textual automatically removes requests based on a configured expiration. The Request Auditor replaces the Request Explorer.