Tonic.ai
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About
Tonic.ai is a comprehensive synthetic data platform designed to equip engineering teams with high-quality, realistic data for development and testing while protecting user privacy. The platform consists of three primary modules: Tonic Structural for de-identifying and synthesizing structured databases, Tonic Fabricate for generating relational data from scratch using agentic AI, and Tonic Textual for redacting sensitive information from unstructured text and logs. By replacing real production data with safe synthetic alternatives, the platform allows organizations to move faster without the security risks associated with data leaks or regulatory non-compliance. The system works by connecting directly to existing data sources such as PostgreSQL, Snowflake, or Databricks. It employs automated privacy scans to detect PII and PHI, then applies sophisticated transformation rules to mask or synthesize values while maintaining the data's original shape and utility. A standout feature is its subsetting capability, which can shrink massive production databases into smaller, manageable datasets while preserving complex referential integrity across multiple tables. Its Fabricate tool utilizes Large Language Models to create relational datasets that mimic real-world patterns even when no production source is available. Tonic.ai is specifically tailored for software engineers, QA professionals, and AI researchers in highly regulated industries like healthcare, finance, and government. These teams often face significant bottlenecks when trying to access realistic data for staging environments or model training due to strict privacy laws. Organizations like eBay, Qualcomm, and Flexport use the platform to streamline their software development lifecycle, enabling faster release cycles and allowing for secure collaboration with offshore development teams without exposing sensitive customer information. What differentiates the platform is its focus on high-fidelity data utility and its ability to handle both structured and unstructured formats within a single ecosystem. It provides the security of on-premise, self-hosted deployments for enterprise clients while holding critical certifications such as SOC 2 Type II and HIPAA compliance. By ensuring that synthetic data behaves exactly like real production data for functional and performance testing, it effectively eliminates the 'data dependencies' that typically slow down enterprise-level innovation.
Pros & Cons
Maintains complex referential integrity when subsetting large databases into manageable test environments.
Certified for high-level security standards including SOC 2 Type II and HIPAA compliance.
Provides a unified platform for handling both structured databases and unstructured text data.
Supports an extensive range of data sources from legacy databases to modern cloud warehouses like Snowflake.
Leverages agentic AI to generate hyper-realistic relational data from scratch without production access.
The Professional pricing tier limits users to only two different data connector types.
Self-hosted deployment options are exclusively reserved for Enterprise-level customers.
Advanced REST API features and workspace inheritance are unavailable on the Professional plan.
Usage on the Professional tier is capped at a maximum of 10TB of source data.
Use Cases
Software engineers can use Tonic Structural to create realistic subsets of production databases, enabling faster local development and more accurate testing.
AI and machine learning researchers can leverage Tonic Textual to safely redact PII from unstructured datasets before using them for model training.
QA teams can automate the hydration of staging environments with fresh, de-identified data that mirrors production complexity to eliminate bugs before release.
Compliance officers can implement automated privacy scans and custom sensitivity rules to ensure all development data meets GDPR and HIPAA standards.
DevOps engineers can integrate synthetic data generation directly into CI/CD pipelines to ensure every test environment is hydrated with safe, high-fidelity data.
Platform
Task
Features
• custom sensitivity rules
• cross-table consistency
• automated privacy scanning
• referential integrity preservation
• database subsetting
• unstructured data redaction
• agentic ai data generation
• structured data de-identification
FAQs
What is the difference between Tonic Structural and Tonic Fabricate?
Tonic Structural is designed to de-identify and synthesize existing production data from databases, whereas Tonic Fabricate uses agentic AI to generate entirely new synthetic data from scratch without needing a production source.
Can I use Tonic.ai to de-identify healthcare data for HIPAA compliance?
Yes, the platform is HIPAA compliant and includes tools for de-identifying protected health information (PHI) with optional expert determination to ensure regulatory standards are met for development and AI workflows.
Does the platform maintain relationships between different database tables?
Yes, Tonic.ai preserves referential integrity and cross-table consistency during synthesis. This ensures that foreign key relationships remain intact, which is critical for functional testing and database subsetting.
What types of databases and files does the platform support?
Supported sources include PostgreSQL, MySQL, SQL Server, MongoDB, Snowflake, BigQuery, and Databricks. It also handles flat files such as JSON, CSV, XML, Parquet, and Avro.
Is it possible to deploy Tonic.ai on-premise?
Self-hosted deployment in a containerized environment is available for Enterprise customers who require the software to run within their own secure infrastructure. Professional plan users are hosted on Tonic Cloud.
Pricing Plans
Professional
Unknown Price• Up to 10TB source data
• 10 Users
• Unlimited workspaces
• Tonic Cloud deployment
• 2 Data connector types
• Basic REST API
• Privacy scan
• Cross-table consistency
• Subsetting with referential integrity
Enterprise
Unknown Price• Unlimited source data
• Unlimited users
• Tonic Cloud or Self-Hosted
• Unlimited data connector types
• Advanced REST API
• Workspace inheritance
• SSO / SAML authentication
• Audit reporting
• Custom sensitivity rules
Free Trial
Free Plan• Experience Tonic Structural
• Standard data generators
• Basic platform features
• No commitment required
Job Opportunities
Partnerships Manager
Generate high-fidelity synthetic data and sanitize production databases to accelerate software development and AI training while ensuring HIPAA and GDPR compliance.
Benefits:
Competitive salary and equity
Unlimited paid time off
401k plan with employer contribution
Medical, dental, and vision insurance
Generous parental leave policy
Experience Requirements:
3–5 years of experience in Partnerships, Channel Sales, Business Development, or Sales role in SaaS
Direct experience navigating AWS, GCP, and Azure cloud providers
Proven track record meeting or exceeding pipeline or partner-influenced revenue targets
Other Requirements:
Exceptional written and verbal communication skills
Self-starter mentality
AI-curious with understanding of data privacy nuances
Relationship-driven with technical competence
Responsibilities:
Manage AWS, Azure, and GCP cloud ecosystem relationships
Execute channel growth with Systems Integrators (SIs), VARs, and resellers
Identify strategic ISVs and draft joint value propositions
Coordinate GTM activities between partner reps and internal Sales/Marketing
Track pipeline and partnership health using Salesforce and partner portals
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Strategic Finance & BizOps Manager
Generate high-fidelity synthetic data and sanitize production databases to accelerate software development and AI training while ensuring HIPAA and GDPR compliance.
Benefits:
Competitive salary and equity
Unlimited paid time off
401k plan with employer contribution
Medical, dental, and vision insurance
Generous parental leave policy
Experience Requirements:
3+ years in GTM/Strategic Finance at tech company, direct investing, or consulting
Fluency in Enterprise SaaS metrics (ARR, NRR, CAC, Magic Number)
World-class financial modeling skills
Other Requirements:
Ability to influence stakeholders without direct authority
Builder mentality for creating processes from scratch
Analytical rigor and ability to translate data into strategic narratives
Responsibilities:
Own company-wide strategic planning, budgeting, and rolling forecasts
Analyze and iterate on pricing and packaging structures
Evaluate growth opportunities including M&A and strategic partnerships
Lead mission-critical special projects for the C-suite and VPs
Prepare Board materials, Investor updates, and track company-wide KPIs
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