Tonic.ai
UnclaimedHigh-fidelity synthetic data generation and transformation for software and AI development.
Visit WebsiteTL;DR - Tonic.ai
- Generates high-fidelity synthetic data from scratch using AI agents.
- De-identifies and transforms sensitive production data while preserving utility.
- Accelerates development, testing, and AI model training while ensuring data privacy and compliance.
Pricing: Free plan available
Best for: Growing teams
4.2/5 across review platforms
Pros & Cons
Pros
- Significantly accelerates development and testing cycles.
- Ensures robust data privacy and compliance without compromising data utility.
- Provides highly realistic and referentially intact synthetic data.
- Reduces critical defects escaping to production.
- Unblocks AI initiatives by safely leveraging sensitive unstructured data.
Cons
- Requires integration into existing development and data workflows.
- May have a learning curve for advanced customization and policy configuration.
- Pricing details are not publicly available, requiring a demo or contact.
Ratings Across the Web
4.2(107 reviews)
Ratings aggregated from independent review platforms. Learn more
Preview
Key Features
AI-powered synthetic data generation (Tonic Fabricate)Production data de-identification and masking (Tonic Structural)Referential integrity preservation across complex schemasData subsetting for smaller, targeted datasetsUnstructured data redaction and synthesis for AI modelsSupport for various databases (Postgres, MySQL, Oracle, SQL Server) and file formats (JSON, PDF, DOCX, EML)Integration into CI/CD pipelinesCompliance with regulations like HIPAA and PCI
Pricing Plans
Free TrialPay-As-You-Go
$19/table/month (after 20 free tables)
- Rapid access to cloud offering
- Ideal for simple use cases and small data sizes
- Monthly credit card subscription
- Billed automatically
- Includes up to 20 unique tables processed per month
- Unlimited processing times for included tables
Professional
Contact us
- Simplest and fastest way to generate highly realistic, privacy-preserving synthetic data
- Access committed spend discounts
- Customer success manager with an annual contract
- Source Data Up to 10TB
- Unlimited Workspaces
- Unlimited Generated Data
- Unlimited Databases
- Tonic Cloud Deployment
- Comprehensive Generator Library
- Privacy Scan
- Cross-Table Consistency
- Schema Change Alerts
- Virtual Foreign Keys
- Concurrent Generations
- Subsetting with Referential Integrity
- Upsert w/o Schema Differences
- Encryption Support
- Generator Presets
- Custom Sensitivity Rules
- Workspace Inheritance
- Choose 2 Data Connector Types
- 10 Users
- Workspace Sharing
- Commenting and Annotation
- Role Based Permissions
- REST API Basic
- Schema Change Alerts Webhooks
- Post Job Actions
- Authentication: Tonic Auth or Google SSO
- Certifications: SOC 2 Type II, AWS Qualified Software, HIPAA Compliant
- Privacy Report
- Audit Report
Enterprise
Contact us
- Complete, self-managed solution
- Enable consistent, unified compliance and streamlined productivity across the organization
- Includes all data and use cases at scale
- Unlimited Source Data
- Unlimited Workspaces
- Unlimited Generated Data
- Unlimited Databases
- Tonic Cloud or Self Hosted Deployment
- Comprehensive Generator Library
- Privacy Scan
- Cross-Table Consistency
- Schema Change Alerts
- Virtual Foreign Keys
- Concurrent Generations
- Subsetting with Referential Integrity
- Upsert w/o Schema Differences
- Encryption Support
- Workspace Inheritance
- Generator Presets
- Custom Sensitivity Rules
- Choose Unlimited Data Connector Types
- Unlimited Users
- Workspace Sharing
- Commenting and Annotation
- Role Based Permissions
- REST API Advanced
- Schema Change Alerts Webhooks
- Post Job Actions
- Authentication: SSO / SAML
- Certifications: SOC 2 Type II, AWS Qualified Software, HIPAA Compliant
- Privacy Report
- Audit Report
Free
Free
- Explore the possibilities of data synthesis via agentic AI
- Trial access to Data Agent
What is Tonic.ai?
Tonic.ai provides advanced synthetic data solutions for software and AI engineers, enabling them to build, test, and train models faster while ensuring data privacy. The platform offers two core products: Tonic Fabricate for generating synthetic data from scratch using AI agents, and Tonic Structural for de-identifying and transforming existing production data. These tools address critical challenges in app development, testing & QA, and AI model training by providing realistic, referentially intact, and privacy-compliant datasets.
Engineers can accelerate product development by eliminating data dependencies, improve testing by fueling staging environments with high-fidelity test data, and unlock sensitive data for AI model training without compromising privacy. Tonic.ai also supports continuous data privacy compliance across various industries, including healthcare, financial services, and government, by offering certified and secure solutions that meet global regulations like HIPAA and PCI.
The platform is designed for engineering teams seeking to enhance developer productivity, achieve faster time-to-market, reduce infrastructure costs, and ensure robust data governance. It integrates seamlessly into CI/CD pipelines and supports a wide range of databases and data formats, making it a versatile solution for modern data workflows.
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Tonic.ai FAQ
How does Tonic Fabricate differ from Tonic Structural in its approach to synthetic data?
Tonic Fabricate generates entirely new synthetic data from scratch using an AI agent, based on natural language prompts, schemas, or sample data. It's ideal for prototyping and new product development where no existing production data is available. Tonic Structural, conversely, transforms existing production data by applying masking, subsetting, and synthesis techniques to de-identify sensitive information while preserving its utility and referential integrity for testing and QA environments.
Can Tonic.ai handle both structured and unstructured data for AI model training?
Yes, Tonic.ai supports both. Tonic Structural can de-identify sensitive structured and semi-structured data from databases. Tonic Textual, a component of the platform, specifically handles unstructured data by detecting, redacting, and synthesizing sensitive information within text, enabling safe use of such data for LLM and AI model training without privacy compromises.
What specific compliance certifications does Tonic.ai hold to ensure data security?
Tonic.ai is SOC 2 certified, demonstrating its commitment to security, availability, processing integrity, confidentiality, and privacy. The platform is also designed to help organizations achieve compliance with regulations such as HIPAA for healthcare data and PCI for financial services data, by providing tools for secure de-identification and transformation.
How does Tonic Structural maintain referential integrity when subsetting or masking large production databases?
Tonic Structural employs advanced algorithms to maintain primary and foreign key relationships across complex database schemas during subsetting and masking operations. This ensures that even when a database is shrunk or sensitive fields are transformed, the data remains consistent and functional, allowing applications and tests to behave as expected without breaking relationships.
Is it possible to integrate the synthetic data generation process directly into a CI/CD pipeline?
Yes, both Tonic Fabricate and Tonic Structural are designed for seamless integration into CI/CD pipelines. This allows for the automated generation and delivery of realistic, privacy-compliant synthetic datasets on demand, accelerating development, testing, and AI workflows by ensuring data is always available when needed.
Can Tonic Fabricate generate synthetic data for niche or highly specialized domains without requiring extensive domain expertise from the user?
Yes, Tonic Fabricate's AI agent is designed to interpret natural language prompts, allowing users to describe the data they need without requiring deep domain expertise. Users can also provide sample data or paste a schema, and the agent will generate relationally intact and domain-specific datasets, which can then be fine-tuned through iterative feedback.
Source: tonic.ai