Overview

Tonic Structural is a synthetic data platform designed to create realistic, privacy-compliant data that mirrors production environments. It empowers engineering teams to safely test, develop, and operate with high-quality synthetic datasets without exposing sensitive information. By combining intelligent data synthesis and structural data modeling, Tonic Structural ensures that generated data maintains referential integrity and realistic relationships. This accelerates development cycles, improves testing reliability, and helps organizations comply with data privacy regulations.

Features and Capabilities

• Synthetic Data Generation: Produces privacy-preserving, realistic synthetic datasets modeled on real production data.
• Structural Data Modeling: Maintains relational integrity and dependencies across complex datasets, ensuring realistic data coherence.
• Privacy Compliance: Automatically removes or masks sensitive information to meet data privacy regulations like GDPR and CCPA.
• Customizable Data Policies: Allows users to define how data fields are transformed or synthesized based on specific compliance needs.
• Rapid Environment Provisioning: Speeds up creation of test and development environments with realistic datasets on demand.
• Data Subsetting: Enables extraction of relevant data subsets to reduce dataset size while preserving data relationships.
• Integration Support: Compatible with multiple databases and development workflows for seamless integration into CI/CD pipelines.
• Audit and Reporting: Tracks data generation activities and transformations for compliance auditing and quality assurance.
• User-Friendly Interface: Intuitive UI and API access to simplify data generation processes for engineering teams.
• Scalability: Designed to handle large-scale data environments suitable for enterprise-grade applications.