Tonic.ai
FreemiumSynthetic data for software and AI development
Tonic.ai is a synthetic data platform that gives engineering and AI teams on-demand access to safe, realistic data for software development, testing, and AI model training. It combines three products: Tonic Fabricate for generating synthetic data from scratch or existing sources, Tonic Structural for de-identifying production data while preserving schema fidelity, and Tonic Textual for redacting and synthesizing unstructured text. Each product includes agentic interfaces that turn manual configuration into conversational workflows.
What is it
A synthetic data platform that generates, de-identifies, and subsets structured and unstructured data so teams can develop, test, and train models without exposing sensitive production information.
What it can do
Create synthetic databases and mock APIs from prompts or schemas, mask and subset production data with referential integrity preserved, redact sensitive entities in documents, and integrate data provisioning into CI/CD pipelines.
Who is it for
Software engineers, QA teams, data engineers, AI/ML practitioners, and compliance-conscious organizations in healthcare, financial services, and other regulated industries.
Key Features
Tonic Fabricate — Synthetic data from scratch or samples
Uses a conversational Data Agent to generate relationally consistent structured data, nested JSON, PDFs, DOCX, EML, and other formats from natural language prompts, uploaded schemas, or existing databases.
Tonic Structural — De-identification with referential integrity
Connects to production databases, detects PII and PHI, applies masking, tokenization, scrambling, and format-preserving encryption, and provisions high-fidelity test data that preserves primary-key and foreign-key relationships.
Tonic Textual — Unstructured data redaction and synthesis
Detects and redacts sensitive entities in free-text, documents, and files, with optional synthetic replacement, to prepare unstructured data for AI development and RAG pipelines.
Data Agent & Validation Agent — Guided, iterative generation
The Data Agent interprets requests and generates data, while the Validation Agent reviews output and prompts refinements until the dataset matches the request.
Use Cases
Secure Software Testing
A QA team provisions masked, production-like test databases for staging so engineers can reproduce bugs without accessing real customer data.
Privacy-Safe AI Model Training
An ML team redacts and synthesizes sensitive documents with Tonic Textual to fine-tune LLMs and build RAG systems without privacy risk.
New Product Development
A startup builds a prototype before production data exists by generating a synthetic database and mock API to unblock frontend and backend work.
Realistic Sales Demos
A sales engineer creates tailored, domain-specific synthetic datasets that demonstrate the product without exposing customer information.
Pricing plans
Frequently Asked Questions
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