Do I own the data I generate with Tonic?

Yes, you retain full ownership of all data you generate. However, Tonic.ai reserves the right to use your conversational prompts and feedback to improve the Data Agent's performance.

What's the difference between Tonic Structural and Tonic Fabricate?

Tonic Structural is for de-identifying and subsetting existing structured production data to create safe test datasets. Tonic Fabricate is for generating entirely new synthetic datasets from scratch, including relational data and unstructured files.

How does usage pricing work for Fabricate?

Usage is measured in tokens (like words or table values). Each conversation turn with the Data Agent consumes tokens based on complexity. Costs vary: a simple correction might be ~$0.17, while refining a complex multi-table schema is ~$0.37.

Can I use my own LLM API key with Fabricate?

Yes, the Enterprise plan for Fabricate offers a 'Bring your own LLM API key' feature, allowing you to use your own LLM endpoints for data generation.

What databases does Tonic Structural support?

It supports a wide range including PostgreSQL, MySQL, SQL Server, MongoDB, Snowflake, BigQuery, Redshift, Databricks, Salesforce, and flat files.

How does Tonic ensure the privacy of the data it processes?

Tonic has a dedicated security posture (trust.tonic.ai) and offers features like privacy scans, audit trails, and encryption support. For Structured, it uses patented algorithms to de-identify data while preserving referential integrity and realism.

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Tonic.ai

Tonic.ai is a synthetic data platform for developers, data engineers, and AI teams. It provides tools to generate realistic test data from scratch or de-identify sensitive production data while preserving structure and relationships. Core products include Fabricate for AI-powered data synthesis via conversational agent, Structural for structured data de-identification, and Textual for unstructured data redaction and synthesis. Targeted at engineering teams in regulated industries like healthcare and finance, it helps accelerate development cycles, unblock QA testing, and enable safe AI model training. The platform supports major databases, file formats, and offers both cloud and self-hosted deployment options.

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Added on

Sep 22, 2026

Synthetic data from scratchData de-identificationText redactionMock APIsLLM privacy proxyTest data managementAI model trainingAgentic AI

Product information

Everything worth knowing about Tonic.ai

The complete picture — from everyday features to the technical detail builders and IT folks dig for.

Core features

What it actually does

AI-Powered Synthetic Data Generation

Generate fully relational databases, unstructured data (PDFs, DOCX), and mock APIs from scratch using a conversational Data Agent powered by LLMs.

Structured Data De-identification

Transform sensitive production data into high-fidelity, referentially intact test data for staging and QA environments.

Unstructured Data Redaction & Synthesis

Safely redact or synthesize sensitive information from unstructured text and files for AI model training and LLM fine-tuning.

Data Discovery & Classification

Scan and identify sensitive data within your datasets using a Privacy Hub and customizable sensitivity rules.

Technical capabilities

Agentic AI Data Agent

Interact via chat to build, iterate, visualize, and refine datasets. Supports Plan Mode for schema planning and a Validation Agent for output checks.

Comprehensive Generator Library

Leverage a library of specialized generators for structured data, including cross-table consistency, referential integrity via patented subsetting, and encryption support.

Must watch videos

3:23

Tutorial3:23

Introducing Tonic.ai: Product Tour

A quick tour of Tonic, the data synthesis platform that enables you to mimic your production data and create safe, useful, de-identified data for QA, testing, and development. Curious to learn more? Let's chat: https://www.tonic.ai/request-a-demo ------ https://www.tonic.ai https://twitter.com/tonicfakedata

Tonic.ai - What is Data De identification

1:21

Tutorial1:21

Tonic.ai - What is Data De identification

Tonic.ai Honest Review - Watch Before Using

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Review2:14

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Who uses it

Real use cases, no hype

AI Model Training

Generate safe, realistic datasets to train and fine-tune LLMs without compromising privacy or compliance.

Software Testing & QA

Create high-fidelity, privacy-safe test data that mirrors production to find bugs faster and release with confidence.

Application Development

Eliminate data dependencies and unblock developers by generating realistic synthetic databases and mock APIs on demand.

Data De-identification

Transform sensitive production data into compliant, shareable datasets for internal use or third-party licensing.

Test Data Management

Automate the creation, subsetting, and refresh of test environments with production-grade, referentially intact data.

LLM Privacy Proxy

Safely use internal data with external LLMs by redacting and synthesizing content before it leaves your environment.

Enterprise Data Licensing

De-identify and package operational data at scale to create new revenue streams through data partnerships.

What's great

Powerful AI-driven synthetic data generation from scratch
Strong structured data de-identification with referential integrity
Comprehensive unstructured data redaction and synthesis

Technical strengths

Wide range of database and file format integrations
Enterprise features: RBAC, SSO, self-hosted deployment
Patented subsetting and cross-table consistency engines

Where it falls short

Custom pricing for core products; no transparent self-serve tiers
Complex, multi-product suite can be confusing to navigate
Enterprise-only features (RBAC, SSO) lock out smaller teams

Technical limitations

Token-based usage model for Fabricate can lead to unpredictable costs
Relies on external LLMs for Fabricate, introducing latency and API dependencies

For technical folks

The deep-dive specs

FAQ

Includes technical Q&A

Tonic Fabricate is an AI-powered tool that generates fully relational databases, unstructured files (like PDFs), and mock APIs from scratch. You interact with a 'Data Agent' via chat to describe what you need, and it uses LLMs and Tonic's synthetic data generators to create realistic data in minutes.