Artificial Intelligence
Tonic.Ai Launches Custom Entity Types In Tonic Textual
Share
New self-serve capability lets users train custom entity detection models on their own data—no data science expertise required.
The feature introduces a fully self-serve workflow for defining and training custom entities—enabling customers to improve or extend Textual’s detection capabilities to serve industry and organization-specific text through an approachable UI. Using large language models (LLMs) for assisted annotation and model distillation, Textual makes it easy for organizations to create high-accuracy, domain-specific models that adapt to their unique data.
#A self-serve breakthrough for sensitive text data
“Custom Entity Types puts the power of model customization directly in the hands of our users,” said Adam Kamor, Co-founder and Head of Engineering at Tonic.ai. “Our customers can now train models and define unique entities themselves—achieving the necessary level of detection and confidence within their workflows—even with highly nuanced text, and without bringing in data science resources.”
Organizations in highly regulated industries such as healthcare, financial services, and legal technology face growing pressure to de-identify sensitive text data while preserving accuracy and context. Custom Entity Types addresses that need by combining a self-serve interface for annotation with private model training, allowing for bespoke detection that’s unique to their specific use case.
# How it works
With Model-Based Custom Entities, users can:
1. Upload documents containing examples of the desired entity type.
2. Leverage LLM-assisted annotation to automatically identify potential entity spans.
3. Review and refine annotations through an intuitive interface.
4. Train a custom entity detection model on their labeled data.
5. Deploy the model securely within their environment for real-time use.
Because the model is trained on the customer’s own data, it achieves exceptional precision and recall for domain-specific entities—whether that’s prescription names and biometric data for healthcare organizations—or unique account information for financial services organizations.
# Accelerating onboarding and adoption
The new capability also accelerates evaluation and onboarding for new customers. Instead of waiting for custom models to be developed by Tonic’s internal team, users can now generate their own entity models during product evaluation—reducing time-to-value and improving adoption rates across enterprise deployments.
“Custom Entity Types not only improves model accuracy—it makes AI data privacy more accessible,” said Whit Moses, Senior Product Marketing Manager at Tonic.ai. “By putting model training in the hands of the user, we’re eliminating a key bottleneck to responsible AI innovation."
Visit the blog for a deeper dive into this new capability. Teams working with unstructured data can try Textual for free or book a demo with an expert at Tonic for a deep dive into the product as it pertains to their specific use case.
# About Tonic.ai
Tonic.ai empowers developers while protecting privacy by enabling companies to create safe, synthetic versions of their data for software testing, model training, and AI implementation. Its platform supports the full spectrum of synthetic data generation—from transforming structured and unstructured production data to generating new datasets from scratch—and integrates seamlessly into modern development and ML workflows. Founded in 2018 by former engineers from Palantir, Tableau, Microsoft, and NVIDIA, Tonic.ai is backed by Insight Partners, Notable Capital, Bloomberg Beta, and SV CISO Investments. The company has offices in San Francisco, Atlanta, New York, and London. For more information, visit Tonic.ai.
Whit Moses, Sr. Product Marketing Manager
TonicAI Inc
whit@tonic.ai
Legal Disclaimer:
EIN Presswire provides this news content "as is" without warranty of any kind. We do not accept any responsibility or liability for the accuracy, content, images, videos, licenses, completeness, legality, or reliability of the information contained in this article. If you have any complaints or copyright issues related to this article, kindly contact the author above.
Frequently Asked Questions
What are Custom Entity Types?
Custom Entity Types is a new feature in Tonic Textual that allows users to build custom entity detection models on their own data, within their own infrastructure or on Tonic’s secure cloud.
How does it work?
Users upload documents, leverage LLM-assisted annotation, refine annotations, train a custom entity detection model, and deploy the model securely.
Why is this important?
It addresses the need to de-identify sensitive text data while preserving accuracy and context, especially in highly regulated industries like healthcare and finance.
First published on Mon, Nov 17, 2025
Liked what you read? That’s only the tip of the tech iceberg!
Explore our vast collection of tech articles including introductory guides, product reviews, trends and more, stay up to date with the latest news, relish thought-provoking interviews and the hottest AI blogs, and tickle your funny bone with hilarious tech memes!
Plus, get access to branded insights from industry-leading global brands through informative white papers, engaging case studies, in-depth reports, enlightening videos and exciting events and webinars.
Dive into TechDogs' treasure trove today and Know Your World of technology like never before!
Disclaimer - Reference to any specific product, software or entity does not constitute an endorsement or recommendation by TechDogs nor should any data or content published be relied upon. The views expressed by TechDogs' members and guests are their own and their appearance on our site does not imply an endorsement of them or any entity they represent. Views and opinions expressed by TechDogs' Authors are those of the Authors and do not necessarily reflect the view of TechDogs or any of its officials. While we aim to provide valuable and helpful information, some content on TechDogs' site may not have been thoroughly reviewed for every detail or aspect. We encourage users to verify any information independently where necessary.
Trending EIN Presswire
Tonic.Ai Launches Custom Entity Types In Tonic Textual
TECH5 And AJARI Partner To Integrate Conversational AI Into The Next Generation DPI
Unifycloud Named A Finalist For The 2025 Microsoft AI Innovation Partner Of The Year Award
Simplifai Appoints Ronald Kasteel, Co-Founder Of Keylane As Chairman Of The Board
Mobilints MLX-A1 Edge AI Box Named CES 2026 Innovation Awards Honoree
Join Our Newsletter
Get weekly news, engaging articles, and career tips-all free!
By subscribing to our newsletter, you're cool with our terms and conditions and agree to our Privacy Policy.
Join The Discussion