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Customer case studies
Ontra accelerates AI innovation in legal tech with Tonic Textual
Ontra is the leader in AI-powered solutions for the private markets. Its AI automates critical private market workflows across the fund lifecycle, enabling firms to accelerate contracts, streamline compliance, and automate entity management. To reinforce its dominant leadership position in the space, Ontra is investing heavily in AI, building purpose-built solutions powered by both commercial LLMs and proprietary models. At the core of this effort is a commitment to protect customer data while ensuring the scalability and velocity of AI development. Tonic Textual has become a foundational part of this strategy by helping Ontra to consistently de-identify and synthesize both structured and unstructured data for safe, scalable AI innovation.
From AI roadblock to breakthrough: how Wellthy transformed healthcare workflows with Tonic.ai
Wellthy, one of the fastest-growing digital healthcare companies in America, was looking to expand their generative AI capabilities but faced challenges due to limited access to realistic data for testing and training. They found the solution they needed with Tonic Textual, enabling them to effectively desensitize their data for secure AI development. The features they've developed using Textual-generated data have helped streamline their in-app messaging workflows and improve their testing environments, leading to better experiences for their members.
How [NAME REDACTED] unblocked AI innovation to optimize tax services, with secure data synthesis from Tonic Textual
[ORGANIZATION] was unable to pursue AI innovations in the tax solutions they offer their clients due to the sensitive nature of the data those workflows would need to access. By deploying Tonic Textual as a privacy layer within LLM workflows to prevent sensitive data from leaking into data models or cloud environments, they unblocked the development of solutions to optimize the efficiency and precision of their services. Tonic Textual enables [ORGANIZATION] to securely handle all of their data through industry-leading accuracy in sensitive data detection and realistic data synthesis, opening the doors to innovation and a stronger competitive edge.
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Patterson cuts test data time by 75% with Tonic.ai, delivering better software for thousands worldwide
Patterson Dental, a division of Patterson Companies (NASDAQ: PDCO), a global organization with 7,600 employees, required high-quality, de-identified, production-like data to utilize for performance and functional testing for its dental provider platforms. The company’s goals included evaluating whether its systems could manage real-world scenarios, identify performance bottlenecks, and reproduce and debug production issues in test environments. By incorporating Tonic Structural into its test data pipeline, Patterson Dental delivered automation, improved debugging efficiency, and enabled its team to focus on delivering a faster, more reliable product for users—all while striving to ensure protected health information (PHI) remained securely out of developer workflows.
Getting eBay developers the data they’re looking for, with Tonic.ai
Using Tonic’s data de-identification tools, eBay shortens development cycles and fuels its automated testing suite. Starting with eBay’s vast data ecosystem of multi PBs spread over multiple data sources, Tonic enables eBay developers to scale their data down to manageable subsets, rapidly protect those subsets with privacy guarantees, and easily call up the exact variety of data they need to hydrate staging, replicate their most complex buyer journeys, and quickly fix bugs found in production.
Everlywell gains 5x deployment velocity with support from Tonic.ai
Tonic has super-charged the feature development cycle at Everlywell, touching every team from development to QA to DevOps and accelerating their release cycle from once a day to 3-5 times a day on average. This new accelerated productivity in development and testing has put Everlywell on a new playing field in terms of meeting consumer demand for online healthcare.
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