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Tonic.ai | Synthetic data solutions for software and AI development

โดย Tonic.ai

Enable your AI and software development workflows with secure, realistic synthetic data.

About 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 agentic solutions for data synthesis, de-identification, and subsetting, our products enable on-demand access to realistic data and simulated worlds for development, testing, and AI model and agent training. The product suite includes Tonic Fabricate for synthetic data generation, Tonic Structural for test data management, and Tonic Textual for unstructured data redaction and synthesis, each equipped with built-in agents to streamline configuration. Unblock innovation, accelerate your engineering velocity, and ship better products, all while safeguarding data privacy.

Solutions


This listing is for private offers only. Please reach out to our team at partnerships-azure@tonic.ai to learn more about our solutions and purchase a license.


Tonic Structural (for structured data)
Tonic Structural is the AI-powered test data management platform for transforming sensitive production data into safe, high-fidelity test data that preserves your data's utility. Through its built-in AI agent and native data connectors, Structural accelerates consistent, secure data masking and synthesis that maintains your data's structure and ensures referential integrity across testing and development environments. By agentifying TDM, Structural turns hours of manual data configuration into minutes. Its patented subsetter equips your developers with targeted, isolated datasets to eliminate collisions in testing. Structural makes enterprise data usable for developers so you can leverage your data effectively to propel innovation.

Tonic Textual (for unstructured data)
Tonic Textual enables teams to put unstructured data to use in AI development while safeguarding against sensitive leaks and ensuring regulatory compliance. Textual extracts free-text from wherever it's stored, detects sensitive information using proprietary NER models, and redacts or synthesizes that information to generate compliant unstructured datasets, ready for use in production or outside of your organization. Through its built-in AI agent, Textual lets you explore dataset contents, configure entity handling, and fine-tune synthesis outputs, replacing hours of manual configuration with a conversation. Use your data confidently in AI development, from internal RAG systems and model training to external partnerships.

Tonic Fabricate (for synthetic data from scratch)
Tonic Fabricate makes generating realistic synthetic data across your entire data ecosystem as simple as asking for it. Within a single agent conversation, connect to live data sources to model from real-world databases, generate datasets from scratch, or combine approaches, creating multiple databases and file formats with referential integrity maintained throughout. Operationalize the results through automated workflows and mock APIs that slot directly into your pipelines. For complex schemas, Fabricate drafts a strategic generation plan giving you control over every step. With Fabricate, developers and AI engineers are free to innovate, unblocking product development, optimizing model and agent training, and accelerating time-to-market.


Benefits of Tonic’s Data Platform

  • Accelerate development and testing: Equip teams with safe, production-like data that speeds releases, powers demos, and eliminates bottlenecks.
  • Fuel AI and analytics with confidence: Provide compliant, de-identified structured and unstructured data for training, evaluation, and RAG pipelines.
  • Support every data need, end to end: From masking to full synthesis, Tonic ensures secure, realistic data across engineering, QA, and data science.

To learn more about our products, see a demo, or speak to a Tonic data protection specialist, please email us at partnerships-azure@tonic.ai.

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