What is synthetic data, and how does Syntho generate it?

Synthetic data is artificially created data that mirrors real-world data's statistical properties without containing actual sensitive information. Syntho uses AI and machine learning models to generate this data, ensuring it closely resembles the original while maintaining privacy.

What are the key benefits of using Syntho's synthetic data generation platform?

The platform offers enhanced privacy by design, compliance with data protection regulations, increased speed and flexibility in data-driven projects, and simplified data collaboration across stakeholders.

How does Syntho ensure the quality of its synthetic data?

Syntho uses stringent quality assurance methods, including data quality metrics and external evaluations, to ensure the synthetic data's accuracy and reliability, aiming to create "synthetic data twins".

What types of data does Syntho support, and what are its limitations?

The platform supports structured, tabular data, including categorical, numerical, and geographic data. However, its suitability for specific data types may require assessment based on individual needs.

How secure is Syntho's platform, and how does it protect sensitive data?

Syntho offers AI-powered PII scanning and smart de-identification features, providing deployment options like on-premise and private cloud to ensure sensitive data never leaves the customer's trusted environment.

What are the different deployment options for Syntho's platform?

Syntho Engine can be deployed on-premise, in a private cloud, or other environments and is packaged in a Docker container for seamless integration.

What is Syntho's pricing model, and what factors influence the cost?

The pricing model is based on features rather than usage. Factors influencing cost include the license tier and additional deployment locations, which determine the features, users, and connectors available.

What kind of support and documentation does Syntho provide?

Comprehensive documentation, a ticket support system, direct communication channels, and personalized onboarding training are provided to assist users effectively.

How long does it take to generate synthetic data using Syntho?

The data generation time is contingent on database size, with tables under 1 million records typically taking less than 5 minutes to process.

What are some examples of how Syntho's synthetic data is used in different industries?

It is utilized in healthcare for AI model training, finance for fraud detection, and various other industries requiring large, realistic datasets for testing, analytics, or AI/ML model development.

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Syntho

Name: Syntho
Brand: Syntho
Availability: InStock
Rating: 5 (1 reviews)
Author: Syntho

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Last updated: October 21, 2024

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What is Syntho?

Syntho is a pioneering company based in Amsterdam, specializing in AI-generated synthetic data that mirrors the statistical properties of real data while maintaining privacy and meeting data protection regulations. Syntho's core solutions include synthetic data for analytics and AI modeling, smart de-identification of sensitive information for compliance, and test data management to support software development without using real production data. The Syntho Engine boasts features like automated de-identification, time-series data synthesis, and rule-based data generation, applicable across various environments through Docker-Compose and Kubernetes. Syntho's integrated platform emphasizes high data accuracy, privacy-centric design, and seamless integration. Its innovations have earned multiple prestigious awards, underscoring Syntho's impact in advancing synthetic data applications across industries.

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Syntho's Top Features

AI-generated synthetic data that reflects real data patterns without containing sensitive information

Smart de-identification features automatically remove or modify Personally Identifiable Information (PII) for privacy compliance

Comprehensive test data management that safeguards sensitive information while supporting software development and testing cycles

The Syntho Engine supports various data types, ensuring ease of deployment and integration

Accurate synthesis of time-series data for time-dependent analyses

Upsampling to address data imbalances and improve data representativeness for machine learning model training

Full data coverage with optimized support for complex data structures

High accuracy of synthetic data, approved by experts at SAS

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