Tonic vs. Syntho

Tonic offers an automated approach to creating mock data that preserves key characteristics of sensitive datasets, which allows developers, data scientists, and sales teams to work efficiently while maintaining confidentiality. By mimicking your production data, Tonic generates de-identified, realistic, and secure datasets that are ideal for testing scenarios. The data is engineered to mirror your actual production datasets, ensuring that the same narrative can be conveyed during testing. With Tonic, users gain access to safe and practical datasets designed to replicate real-world data on a large scale. This tool not only generates data that looks like production data but also acts in a similar manner, enabling secure sharing across teams, organizations, and international borders. It incorporates features for detecting, obfuscating, and transforming personally identifiable information (PII) and protected health information (PHI). Additionally, Tonic actively protects sensitive data through features like automatic scanning, real-time alerts, de-identification processes, and mathematical guarantees of data privacy. It also provides advanced subsetting options compatible with a variety of database types. Furthermore, Tonic enhances collaboration, compliance, and data workflows while delivering a fully automated experience to boost productivity. With its extensive range of features, Tonic emerges as a vital solution for organizations navigating the complexities of data security and usability, ensuring they can handle sensitive information with confidence. This makes Tonic not just a tool, but a critical component in the modern data management landscape.

Syntho is typically deployed within the secure infrastructures of our clients to ensure that confidential data stays within a reliable framework. Our pre-built connectors facilitate seamless integration with both source data and target systems with minimal effort. We offer compatibility with all major database platforms and file systems, featuring over 20 connectors for databases and more than 5 for file systems. Clients can choose their preferred method for data synthesis, allowing options such as realistic masking or the creation of entirely new values, while also enabling the automatic identification of sensitive data types. After safeguarding the data, it can be shared and utilized with confidence, maintaining compliance and privacy regulations throughout its entire lifecycle. This not only promotes a secure approach to data management but also encourages a culture of trust and accountability in handling sensitive information.