Tool Information
Syntho is a self-service platform specializing in the generation of synthetic data to accelerate data-driven solutions. Synthetic data mimics the statistical patterns of original data, substituting sensitive personally identifiable information (PII), making it invaluable for privacy-conscious segments like healthcare and finance. Syntho's software offers several options for test data management, enabling users to generate synthetic data based on rules and constraints, de-identify and synthesize test data that reflects production data, and create representative subsets from a relational database. Beyond data generation, Syntho is also capable of smart de-identification, using an AI-powered PII scanner to automatically identify and modify sensitive data. Users can assess the quality of generated synthetic data in terms of accuracy and speed, with external validation available from SAS. The platform also offers time series synthetic data synthesis and synthetic mock data generation capabilities, preserving the integrity of relational data ecosystems despite alterations. The platforms 'Syntho Engine' supports a variety of data types and offers features such as deployment and integration assistance, and source data and target environment connectors. User documentation and support are provided to guide usage, while live demos are available for those seeking visual assistance with the tool.
F.A.Q (20)
Syntho is a self-service platform that generates high-quality synthetic data using artificial intelligence (AI) technology. Synthetic data, acting as an alternative to real-world data, allows for the construction of strong data foundations, the creation of enhanced product demos, and the acceleration of application testing-all without infringing on privacy or confidentiality. Syntho's platform supports various features, including the Syntho Engine responsible for data generation, a PII scanner for tackling sensitive information exposure, and offering several pricing plans to meet diverse user requirements.
Syntho leverages AI to generate synthetic data that mirrors the statistical patterns found in original data. These artificial data sets are made devoid of sensitive personally identifiable information (PII), making them suitable for sectors requiring privacy, like healthcare and finance. Users have the option to produce synthetic data according to certain rules and constraints, creating test data reflecting production data, and forming smaller representative subsets from a larger relational database.
The Syntho Engine is the core of Syntho's synthetic data generation. It creates synthetic data, compatible with diverse data types and complex structures like time series data. It also comes equipped with extended features such as deployment and integration assistance, and connectors for source data and target environment. Along with these, options for quality assurance, external validation by data experts from SAS, time series data synthesis, and synthetic mock data generation are also offered.
Syntho employs AI technology to uphold the integrity, safety, and accuracy of the synthetic data it generates. Even as it mimics the statistical patterns of original data, sensitive personally identifiable information (PII) is carefully substituted to preserve privacy. It also offers an AI-powered PII scanner that automatically identifies and modifies sensitive data, adding an extra layer of security. An external validation by SAS is available, allowing users to assess the quality of the synthetic data in terms of accuracy, privacy, and speed.
Syntho’s synthetic data can be utilized in various business scenarios like faster software solutions delivery, building robust data foundations for analytics, resolving data sharing challenges, creating impressively tailored product demos, unlocking potential revenue by using synthetic data for privacy-compliant insights, and enabling rapid prototyping and hypothesis validation before real data request performance. It helps sectors such as healthcare, finance, and public organizations to benefit from higher quality, faster, and privacy-compliant data.
Yes, synthetic data generated by Syntho is trustable. The platform has mechanisms in place to ensure the accuracy, privacy, and speed of the data generated are of high quality. External validation is also available from SAS to further attest to its high accuracy. Furthermore, the AI-powered PII scanner substitutes sensitive data with synthetic data, ensuring privacy and confidentiality.
Syntho's synthetic data can provide significant benefits across a range of sectors including healthcare, finance, and public organizations. It allows these sectors to expedite testing applications, build robust data foundations, and create impressive product demos without compromising privacy or revealing sensitive data. Moreover, through using synthetic data, these sectors can quickly validate assumptions and experiment with data-driven solutions.
Syntho offers various career opportunities for aspirants interested in working in the sphere of synthetic data. The platform provides information about its team, company values, and the integral role each team member plays in delivering this innovative service.
Syntho’s pricing plans are designed to cater to the varying needs of subscribers. It operates on a monthly license model based not on the volume of data produced, but the features that users require. The aim is to generate unlimited data at a fixed price, allowing organizations to choose the plan that best fits their needs.
The PII scanner offered by Syntho is an AI-powered tool designed to identify sensitive personal information within datasets or databases. This scanner works to prevent the exposure of sensitive personal information, automatically identifying and modifying such data, thus providing an additional layer of security to the synthetic data generation process.
Syntho's synthetic data can significantly speed up data-driven tech solutions by providing an instant, high-quality data source for testing applications, building strong data foundations, and creating next-level product demos, all without compromising privacy or confidentiality. Since the data generated by Syntho mimics the statistical patterns found in original data, teams can operate knowing that their decision-making or research is based on accurate, reliable data.
Syntho treats sensitive personally identifiable information (PII) with utmost priority. It substitutes sensitive PII with synthetic data that mirrors the statistical patterns of the original data. Further, it offers a Smart De-Identification feature and an AI-powered PII scanner that automatically identifies and modifies sensitive data, ensuring no sensitive personal information is exposed.
Syntho provides a range of options for test data management such as de-identification and synthetization, rule-based synthetic data generation, and subsetting (creating a smaller, representative subset from a large relational database). These options enable users to create, maintain, and control representative test data for non-production environments.
Smart De-Identification in Syntho involves protecting sensitive information by removing or modifying personally identifiable information. It uses an AI-powered PII scanner to identify PII automatically, thus preventing the exposure of sensitive personal information through datasets or databases.
Yes, Syntho provides options to assess the quality of generated synthetic data in terms of accuracy and speed. It has an in-built quality assurance report, and for further validation, it offers an external evaluative check by the data experts of SAS.
Time series synthetic data synthesis in Syntho involves accurately synthesizing time-series data with Syntho. This feature allows it to handle complex data structures and ensure integrity across time-bound data series despite alterations.
Synthetic mock data generation in Syntho involves the substitution of sensitive personally identifiable information (PII), Protected Health Information (PHI), and other identifiers to generate mock data that accurately mirrors the statistical patterns of original data while maintaining privacy.
The Syntho Engine supports a variety of data types. It is optimized to handle the most complex structures, such as time series data, thus ensuring it can cater to diverse datasets depending on the specific user needs.
Syntho provides adequate user documentation to guide usage of its platform. To ensure users have an optimal experience, it offers comprehensive guides, whitepapers, blogs, and case studies. Additionally, users can register for live webinars or explore archived sessions.
Yes, Syntho offers the ability to schedule a live demo with their experts. This feature allows users to understand the nuances of the tool better and witness its working in real-time, enhancing their understanding and enabling better usage of the platform.
Pros and Cons
Pros
- Generates synthetic data
- Self-service platform
- Extended support features
- Ensures accuracy and safety
- Useful for product demos
- PII scanner feature
- Useful for data-driven solutions
- Generates rule-based data
- Ability to de-identify data
- Supports various datasets
- Offers time-series synthetic data
- Designed for different sectors
- Provides user documentation
- Offers live demos
- SAS validated the quality
- Preserves data ecosystem integrity
- Deployment and integration assistance provided
- Fast and high-quality data generation
- Aids in data de-identification
- Enables privacy-preserving data sharing
- Supports experimentation and prototyping
- Facilitates system migration scenarios
- Test data management options
- Quality assurance report for assessment
Cons
- No free trial
- Pricing plans unclear
- Limited data type support
- Might oversimplify complex data
- Reliability on external validation
- No explicit data security measures
- Limited on-premise deployment support
- No specific market focus
- Limited advanced feature set
- Heavily reliant on user-set rules
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