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Syntho is a synthetic test data management platform designed to generate realistic, privacy-preserving synthetic data that mimics real data safely and efficiently. Developed to address challenges related to using sensitive real data, Syntho combines multiple synthetic data generation methods including Synthetic Data Masking, Rule-Based Synthetic Data, and AI-Generated Synthetic Data in one unified platform. This flexibility allows users to tailor data generation to specific use cases, ensuring data privacy while maintaining data utility. Syntho is ideal for organizations needing production-like test data, faster product development cycles, secure data sharing, and enhanced analytics or AI modeling. It supports both technical and non-technical users by providing an easy-to-use interface and API, and can be deployed securely within the user’s own environment to maintain full control over data privacy. Syntho fits workflows in software testing, data analytics, AI model validation, and secure data collaboration across industries.
4.7/5
Realistic, privacy-preserving, and customizable
User-friendly with API and UI options
To generate realistic synthetic data that preserves privacy for testing, analytics, and AI modeling.
Deployable in own environment with connectors for databases and API integration for workflow automation.
Transparent pricing with no usage-based fees, offering flexible plans.
Features with the highest value for users are highlighted here.
Synthetic Data Masking
Rule-Based Synthetic Data Generation
AI-Generated Synthetic Data
PII Scanning and Removal
Consistent Data Mapping
Automated Data Generation Workflows
Deployment in User Environment
API and User Interface Access
Software Testers
Data Scientists
Product Managers
Compliance Officers
Analytics Teams
Small to Medium Enterprises
Large Enterprises
AI Researchers
Demo and Sales Teams
Data Engineers
Starter
Pro
Weekly intelligence on AI strategy, operations, and market shifts. No noise. No narrative. Direct to your inbox.
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