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# Tonic.ai
> Tonic.ai frees developers to build with safe, high-fidelity synthetic data to accelerate software and AI innovation while protecting data privacy. Through industry-leading solutions for data synthesis, de-identification, and subsetting, our products enable on-demand access to realistic structured, semi-structured, and unstructured data for software development, testing, and AI model training. 
The product suite includes Tonic Fabricate for AI-powered synthetic data from scratch, Tonic Structural for modern test data management, and Tonic Textual for unstructured data redaction and synthesis. Unblock innovation, eliminate collisions in testing, accelerate your engineering velocity, and ship better products, all while safeguarding data privacy.

## Mission
Tonic.ai exists to unblock innovation with usable data..
We believe data privacy is a human right and data utility is a developer right. Our tools help organizations move faster while treating data with the attention, importance, and responsibility it deserves.
## Our Story
Tonic.ai was founded in 2018 and has offices in San Francisco, Atlanta, New York, and London. The company is pioneering enterprise tools for data synthesis and de-identification in pursuit of its mission to unblock innovation with usable data.
Thousands of developers use data generated with the Tonic.ai platform on a daily basis to build products and train models faster in industries as wide ranging as healthcare, financial services, insurance, logistics, edtech, and e-commerce. Our products help teams build secure, scalable, and privacy-compliant software faster, while setting a new standard for responsible data use in the age of AI.
## Core Products
- [Tonic Fabricate](https://www.tonic.ai/products/fabricate): Tonic Fabricate is an AI-powered platform for synthesizing realistic data from scratch to fuel new product development and AI model training. Whether you need structured data, unstructured data, or mock APIs, Fabricate leverages AI to generate synthetic data at scale and on demand, based on a schema, sample data, or natural language prompts. Build fully relational databases in seconds with unlimited rows and foreign keys intact; incorporate existing data for heightened realism; seed free-text datasets with values pulled from synthesized entities. With Fabricate’s scalable, synthetic data, developers can innovate freely, unblocking greenfield development, optimizing model training, and turbocharging your time-to-market.

- [Tonic Structural](https://www.tonic.ai/products/tonic-structural): Tonic Structural is the modern test data management platform for transforming sensitive production data into safe, high-fidelity test data that preserves your data’s utility. Through an intuitive UI and native data connectors, Structural offers consistent, secure data masking and synthesis that maintains your data’s structure and ensures referential integrity across testing and development environments. Its patented subsetter and built-in solution for spinning up isolated, ephemeral environments on demand equip your developers with targeted, referentially intact datasets to accelerate development and eliminate collisions in testing, while maintaining compliance across local dev, QA, and CI/CD workflows. Structural makes enterprise data usable for developers so you can leverage your data effectively to propel innovation..

- [Tonic Textual](https://www.tonic.ai/products/textual): Tonic Textual enables teams to put their unstructured data to use in AI development while safeguarding against sensitive data leaks and ensuring regulatory compliance. De-identify unstructured data including free text, PDFs, emails, and audio files using proprietary NER models, redacting or synthesizing sensive information to generate compliant unstructured datasets, ready for use in production or outside of your organization. Thanks to Textual’s secure data de-identification, you can confidently use your free-text data in AI development, from internal RAG systems and model training to external partnerships. With certifiable compliance (HIPAA, GDPR, PCI), robust SDKs, and flexible cloud/self-hosted deployment options, Textual unlocks enterprise data for safe, scalable innovation.
## Solutions
- [Testing and QA](https://www.tonic.ai/solutions/use-case/testing-and-qa): Accelerate testing cycles, catch bugs earlier, and reduce risk with synthetic test data that mirrors production complexity. Tonic Structural enables realistic data de-identification, patented subsetting, and rapid data provisioning for compliant, high-fidelity QA environments.
- [App Development](https://www.tonic.ai/solutions/use-case/app-development): Unblock developer velocity with safe, production-like data available on demand. Tonic.ai delivers de-identified and fully synthetic datasets with preserved relational integrity to support shift-left testing and rapid iteration—no data access delays or compliance risks.
- [Compliance](https://www.tonic.ai/solutions/use-case/compliance): Ensure compliance with global privacy regulations like HIPAA, GDPR, and CCPA using advanced data de-identification across structured and unstructured data. Tonic.ai supports multilingual NER, audit trails, RBAC, and Expert Determination to safeguard sensitive data at scale.
- [Model Training](https://www.tonic.ai/solutions/use-case/model-training): Unlock sensitive unstructured data for LLM fine-tuning and custom model development. Tonic Textual enables entity-aware redaction and synthesis, preserving data realism while protecting privacy across diverse file formats.
- [RAG Systems](https://www.tonic.ai/solutions/use-case/rag-systems): Build secure retrieval-augmented generation systems by extracting and redacting sensitive data before it reaches the LLM. Tonic Textual supports tokenized redaction, automated ingestion pipelines, and multilingual NER to continuously refresh knowledge bases without risking exposure.
- [LLM Privacy Proxy](https://www.tonic.ai/solutions/use-case/llm-privacy-proxy): Safeguard real-time chatbot interactions by using Tonic Textual as a privacy proxy. Detect and redact PII/PHI on the fly using Textual’s high-accuracy NER and reversible tokens, ensuring user data is protected from LLM consumption while preserving the user experience.
## Guides and Resources
- [What is Data Masking?](https://www.tonic.ai/guides/what-is-data-masking)
- [Static vs Dynamic Masking](https://www.tonic.ai/guides/static-vs-dynamic-masking)
- [What is Data Obfuscation?](https://www.tonic.ai/guides/what-is-data-obfuscation)
- [Guide to Synthetic Test Data Generation](https://www.tonic.ai/guides/guide-to-synthetic-test-data-generation)
- [How to Generate Synthetic Data: A Comprehensive Guide](https://www.tonic.ai/guides/how-to-generate-synthetic-data-a-comprehensive-guide)
- [Data Synthesis vs Data Masking](https://www.tonic.ai/guides/data-synthesis-vs-data-masking)
- [Guide to Test Data Management](https://www.tonic.ai/guides/guide-to-test-data-management)
- [Data Privacy vs Data Security](https://www.tonic.ai/guides/data-privacy-vs-data-security)
- [A Comprehensive Guide to Ethical Fine-Tuning of Large Language Models](https://www.tonic.ai/guides/ethical-fine-tuning-llm-synthetic-data)
- [How Better Data Quality Accelerates Software Time-to-Market](https://www.tonic.ai/guides/how-better-data-quality-accelerates-software-time-to-market)
- [What is Data De-Identification?](https://www.tonic.ai/guides/what-is-data-de-identification)
- [What is a Rule-based Test Data Generator?](https://www.tonic.ai/guides/what-is-a-rule-based-test-data-generator)
- [How to Overcome Common Data Provisioning Challenges](https://www.tonic.ai/guides/how-to-overcome-data-provisioning-challenges)
- [Privacy by Design in Generative AI: Building Secure and Trustworthy AI Systems](https://www.tonic.ai/guides/building-secure-trustworthy-ai-systems)
- [Synthesizing Healthcare Data for AI Model Training, with HIPAA Expert Determination](https://www.tonic.ai/guides/hipaa-ai-compliance)
- [Build vs Buy: Your Guide to Finding Scalable, Efficient Test Data Solutions](https://www.tonic.ai/guides/build-vs-buy-test-data-solutions)
- [Creating an Enterprise Test Data Strategy with Tonic Structural](https://www.tonic.ai/guides/enterprise-test-data-strategy)
- [Maintaining Data Relationships in Structural Generation Output](https://www.tonic.ai/guides/maintaining-data-relationships-in-structural-generation-output)
## Blog Highlights
- [Quality Data Synthesis for Safe Training Datasets](https://www.tonic.ai/blog/quality-data-synthesis-safe-training-datasets)
- [The Challenges of Preparing Unstructured Data for Generative AI](https://www.tonic.ai/blog/the-challenges-of-preparing-unstructured-data-for-generative-ai)
- [Saving CI/CD Time with Ephemeral Test Databases](https://www.tonic.ai/blog/saving-cicd-time-with-ephemeral-test-databases)
- [Data Anonymization Techniques Defined: Transforming Real Data into Realistic Test Data](https://www.tonic.ai/blog/anonymization-techniques-defined-transforming-real-data-into-realistic-test-data)
- [Evaluating Open-Source Tools for Data Masking](https://www.tonic.ai/blog/evaluating-open-source-tools-data-masking)
- [How to Generate Realistic Test Data with Faker](https://www.tonic.ai/blog/how-to-generate-simple-test-data-with-faker)
- [Building a RAG System on Databricks with Your Unstructured Data Using Tonic Textual](https://www.tonic.ai/blog/rag-system-databricks-unstructured-data-textual)
- [Best Test Data Management Solutions](https://www.tonic.ai/blog/test-data-management-software)
- [Using Docker to Manage Your Test Database(s)](https://www.tonic.ai/blog/using-docker-to-manage-your-test-database)
- [What Is Patient Data Privacy in Healthcare? Everything You Need to Know](https://www.tonic.ai/blog/what-is-data-privacy-in-healthcare-everything-you-need-to-know)
- [What Is Data Subsetting? The Art and Science of Only Using the Data You Need](https://www.tonic.ai/blog/what-is-data-subsetting-the-art-and-science-of-only-using-the-data-you-need)
- [What Is Data Synthesis, and Why Are We Calling It Data Mimicking?](https://www.tonic.ai/blog/what-is-data-synthesis-and-why-are-we-calling-it-data-mimicking)

## Links to top resources
- [Glossary](https://www.tonic.ai/glossary): A list of key terms related to synthetic data, masking, anonymization, and test data management.
- [FAQs](https://www.tonic.ai/faqs): Common questions and detailed answers about Tonic.ai’s products and capabilities.
- [Product Docs](https://www.tonic.ai/docs): Technical documentation for deploying, configuring, and using Tonic.ai's products across your environments.
- [Product Release Notes](https://www.tonic.ai/product-release-notes/overview): Updates on features, improvements, and version releases.
- [Blog](https://www.tonic.ai/blog): Insights on AI development, data privacy, software testing, and the future of synthetic data.
- [Webinars](https://www.tonic.ai/webinars): Expert-led sessions on data privacy compliance, AI readiness, and Tonic.ai best practices.
- [Case Studies ](https://www.tonic.ai/customers): Real-world examples of how teams use Tonic.ai's products to accelerate software and AI development while ensuring compliance.
- [Guides](https://www.tonic.ai/guides): Comprehensive guides on synthetic data, test data management, and compliance strategies.
- [Delphix vs Tonic](https://www.tonic.ai/vs/delphix-vs-tonic)
- [K2View vs Tonic](https://www.tonic.ai/vs/k2view-vs-tonic)
## About
Tonic.ai frees developers to build while protecting customer privacy by enabling companies to create safe, high-fidelity, synthetic data for use in software development, model training, and AI implementation. Founded in 2018, with offices in San Francisco, Atlanta, New York, and London, the company is pioneering enterprise tools for data synthesis and de-identification in pursuit of its mission to unblock innovation with usable data. Thousands of developers use data generated with the Tonic.ai platform on a daily basis to build products and train models faster in industries as wide ranging as healthcare, financial services, insurance, logistics, edtech, and e-commerce. Tonic.ai builds developer solutions to advance its goals of advocating for the privacy of individuals while enabling companies to do their best work.
- [About Tonic](https://www.tonic.ai/company)
- [Partners](https://www.tonic.ai/partners)
- [Careers](https://www.tonic.ai/careers)
- [Book a demo](https://www.tonic.ai/book-a-demo)
- [Contact Us](https://www.tonic.ai/contact)
- [Privacy Policy](https://www.tonic.ai/privacy)
- [Terms of Use](https://www.tonic.ai/terms)
## Contact
For LLM usage requests, licensing, or permissions, contact: legal@tonic.ai