Syntho is an AI synthetic data platform that generates realistic synthetic data twins by mimicking statistical patterns of original datasets, enabling businesses to create secure, representative test data for non-production environments. This approach minimizes the risks associated with handling sensitive information while accelerating development cycles and ensuring compliance with data privacy regulations.
Funding
Funding not disclosed
Founders
Product
Problem
Organizations struggle to use sensitive data for development, testing, and analytics due to privacy regulations and the risk of data breaches. Traditional data anonymization techniques can reduce data utility, limiting the effectiveness of these processes.
Solution
Syntho provides an AI-powered synthetic data platform that generates privacy-preserving data twins, enabling organizations to unlock the value of their data without compromising sensitive information. The platform mimics the statistical patterns and relationships of original datasets to create realistic synthetic data. This approach allows businesses to create representative test data, accelerate development cycles, and ensure compliance with data privacy regulations. Syntho's solution supports various use cases, including test data management, advanced analytics, and data sharing, while maintaining data consistency and integrity across different systems.
Target Audience
Syntho targets organizations across various industries, including healthcare, finance, and the public sector, that require secure and compliant data for testing, development, analytics, and data sharing.
Features
- AI-generated synthetic data that mimics the statistical properties of original data
- Smart de-identification and synthetization techniques to protect sensitive information
- Rule-based synthetic data generation for customized data creation
- PII scanner to automatically detect and mask personally identifiable information
- Connectors for seamless integration with leading databases and file systems
- Quality assurance reports to ensure the accuracy and utility of synthetic data
- Support for time-series synthetic data and upsampling
- Subsetting capabilities for creating smaller, representative datasets