Quick Summary
Tonic.ai has released several product updates in January 2026 aimed at enhancing user experience. Key updates include the introduction of Guided Redaction in Textual, allowing for improved sensitive data handling, and the ability to build custom detection models. Additionally, Tonic has published a white paper benchmarking its Textual product against competitors, demonstrating superior performance in sensitive text identification. These updates are significant for organizations handling sensitive information, as they enhance compliance and data protection capabilities.
The Securityish Brief
Tonic.ai has introduced several notable updates in January 2026 to improve its product offerings. Among these is the beta launch of Guided Redaction in Textual, which integrates AI-powered sensitive data detection with a human review process. This feature is designed for teams that require meticulous redaction of sensitive information, ensuring compliance and accuracy in handling regulated documents and customer records.
Another significant update is the rollout of Model-based Custom Entity Types, which allows users to create and train detection models tailored to their specific data needs. This flexibility enables teams to optimize detection for unique terminologies relevant to their industries, such as medical or legal terms.
Tonic has also published a white paper titled ‘Sensitive Text Identification: Industry Landscape and Performance Benchmarking.’ This document evaluates Tonic Textual against various competitors, including AWS Comprehend and Google Cloud DLP, revealing that Tonic consistently achieves high precision and recall scores across diverse datasets.
In addition to these major features, Tonic Structural now automates schema changes by auto-applying generators, which streamlines the data generation process and enhances continuous integration and delivery (CI/CD) pipelines. This update minimizes manual configuration efforts and improves operational efficiency.
Lastly, Tonic Fabricate has expanded its data export capabilities, allowing users to export generated data in any text-based file format, enhancing usability and flexibility for various applications.
Key Product Updates
- Guided Redaction in Textual: A beta feature that combines AI detection with human review for sensitive data redaction.
- Model-based Custom Entity Types: Users can build and train detection models tailored to their specific data requirements.
- White Paper: ‘Sensitive Text Identification’ benchmarks Tonic Textual against competitors, highlighting its superior performance.
- Auto-applying generators in Structural: Automates schema changes to improve CI/CD pipeline efficiency.
- Exporting data from Fabricate: Users can now export generated data in any text-based file format.
Key Takeaways
- Explore the new Guided Redaction feature in Tonic Textual to enhance your sensitive data handling processes.
- Consider building custom detection models using Model-based Custom Entity Types to better suit your organization’s specific data needs.
- Review the white paper on sensitive text identification to understand how Tonic Textual compares to other solutions.
- Utilize the auto-applying generators feature in Tonic Structural to streamline your CI/CD pipelines.
- Take advantage of the expanded data export capabilities in Tonic Fabricate to meet diverse data format requirements.
Key Terms & Concepts
- Guided Redaction: In this article, Guided Redaction refers to a new feature in Tonic Textual that combines AI detection with human review for sensitive data redaction.
- Model-based Custom Entity Types: This term describes a feature that allows users to create and train detection models tailored to their specific data needs within Tonic Textual.
- CI/CD pipelines: In this context, CI/CD pipelines refer to the processes that automate the integration and delivery of software changes.
- Tonic Fabricate: Tonic Fabricate is a product that allows users to generate and export data in various formats, enhancing flexibility in data management.
- White Paper: A white paper is a research-backed document published by Tonic that benchmarks its Textual product against competitors in sensitive text identification.
Read the original article here: https://securityboulevard.com/2026/01/tonic-ai-product-updates-january-2026/
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