Agentic synthetic data generation
Use the Data Agent to chat with the system, iterate on a dataset, and generate synthetic data for relational databases or unstructured files.
Tonic.ai
RevendiquerTonic.ai is a synthetic data platform for software development, testing, and AI workflows. Generate realistic data, protect sensitive information, and support privacy-aware development.
Overview
Tonic.ai is a synthetic data platform for software development, testing, and AI workflows. The product suite combines synthetic data generation, structured test data management, and unstructured data de-identification so teams can work with realistic data without exposing sensitive information.
The platform is organized around three main products: Tonic Fabricate for AI-powered synthetic data generation, Tonic Structural for test data synthesis and management, and Tonic Textual for unstructured data de-identification. Across these products, the site emphasizes production-like data, privacy controls, and deployment options that support both cloud and enterprise use cases.
Features
Structured test data workflows
Generate structured test data with support for referential integrity, patented subsetting, cross-table consistency, and schema change alerts.
Privacy and protection controls
Scan and protect sensitive data with privacy reports, audit trails, sensitivity rules, and automatic redaction or reversible tokenization.
Wide source and export support
Support a broad set of database sources and export paths, including PostgreSQL, MySQL, MongoDB, Snowflake, BigQuery, Databricks, and more.
AI-ready data preparation
Adapt outputs to AI workflows with entity metadata tags, realistic synthesis, mock APIs, and pipelines for RAG or LLM use cases.
Enterprise administration
Use enterprise controls such as RBAC, SSO, centralized billing, multiple workspaces, and self-hosted deployment where available.
Use Cases
Application development with safe data
Generate production-like synthetic databases or unstructured files when teams need realistic data for product development but cannot use live records.
Testing and QA
Substitute high-fidelity test data into staging and QA environments to improve release testing while preserving referential integrity and privacy.
AI model training and LLM workflows
Detect, redact, or synthesize sensitive entities in unstructured datasets before using them for fine-tuning, prompt workflows, or retrieval systems.
Reinforcement learning environments
Build realistic simulated environments for reinforcement learning using synthetic data, personas, tasks, and live APIs that mirror real-world complexity.
Enterprise governance and collaboration
Use enterprise controls such as RBAC, SSO, centralized billing, and self-hosted deployment to manage synthetic data workflows across larger teams.
Pros and Cons
Pros
- Covers both structured and unstructured data workflows in one platform.
- Supports realistic synthetic data generation for development, QA, and AI model training.
- Includes privacy-focused controls such as redaction, synthesis, privacy scans, and audit trails.
- Offers multiple pricing paths, including a free tier for Fabricate and enterprise contact-sales plans.
- Provides deployment options that include Tonic Cloud and, for some plans, self-hosted setups.
Cons
- Some capabilities are described at a high level on the public site, so workflow depth and implementation detail are limited from the available evidence.
- Several deployment, integration, and connector details are not fully documented in the collected source text.
FAQ
What does Tonic.ai provide?
Tonic.ai offers a suite of products for synthetic data generation and sensitive data de-identification. Tonic Fabricate is positioned for generating synthetic data through an agentic Data Agent; Tonic Structural focuses on test data management and synthesis; and Tonic Textual handles unstructured data de-identification for AI workflows.
What is Tonic Fabricate used for?
Tonic Fabricate is designed to generate realistic synthetic data from prompts, including relational databases and unstructured formats such as PDFs and DOCX files. The pricing page also describes a free tier, a paid individual plan, and enterprise pricing.
What does Tonic Structural do?
Tonic Structural supports structured test data workflows, including generation, subsetting, privacy scanning, referential integrity, schema change alerts, and export options for common databases. It is aimed at teams that need production-like test data for development and QA.
What is Tonic Textual used for?
Tonic Textual is built for unstructured data de-identification. It can detect sensitive entities, redact or synthesize them, and support use cases like AI model training, RAG systems, LLM prompts, and lower environments.
Does Tonic.ai have free or enterprise pricing?
Pricing is offered across free, paid, and enterprise paths depending on the product. Fabricate has a free tier and a $29/month plan for individuals, while Structural and Textual include enterprise options with contact-sales pricing.
Quick Facts
- Category
- Synthetic data platform
- Primary products
- Tonic Fabricate, Tonic Structural, Tonic Textual
- Main use
- Software development, testing, and AI data workflows
- Deployment
- Tonic Cloud; self-hosted for some enterprise plans
- Pricing
- Free and paid plans for Fabricate; enterprise contact-sales pricing on other offerings
- Source domain
- tonic.ai