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What is Syntheticus?

Syntheticus® transforms the landscape of data exchange for organizations by tackling issues of accessibility, scarcity, and bias on a grand scale. Our platform for synthetic data empowers you to generate high-quality data samples that are compliant and tailored to fit your unique business goals and analytical needs. By leveraging synthetic data, you can tap into a wide range of valuable sources that may not be easily accessible in the real world. This enhanced access to quality, consistent data bolsters the dependability of your research, leading to better products, services, and decision-making strategies. With reliable data resources at your disposal, you can accelerate product development timelines and fine-tune your market entry strategies. Moreover, synthetic data is crafted with privacy and security at the forefront, protecting sensitive information while complying with applicable privacy laws and regulations. This innovative approach not only reduces potential risks but also equips businesses with the confidence to pursue new ideas and advancements. As a result, organizations can stay competitive in a rapidly evolving market landscape.

What is GenRocket?

Solutions for synthetic test data in enterprises are crucial for ensuring that the test data mirrors the architecture of your database or application accurately. This necessitates that you can easily design and maintain your projects effectively. It's important to uphold the referential integrity of various relationships, such as parent, child, and sibling relations, across different data domains within a single application database or even across various databases used by multiple applications. Moreover, maintaining consistency and integrity of synthetic attributes across diverse applications, data sources, and targets is vital. For instance, a customer's name should consistently correspond to the same customer ID across numerous simulated transactions generated in real-time. Customers must be able to swiftly and accurately construct their data models for testing projects. GenRocket provides ten distinct methods for establishing your data model, including XTS, DDL, Scratchpad, Presets, XSD, CSV, YAML, JSON, Spark Schema, and Salesforce, ensuring flexibility and adaptability in data management processes. These various methods empower users to choose the best fit for their specific testing needs and project requirements.

Media

Media

Integrations Supported

Integrations Supported

Amazon Web Services (AWS)
BlazeMeter
CA Flowdock
Chef
Cucumber
DXC Cloud
Delphix
Docker
FitNesse
Gerrit Code Review
Git
HCL Accelerate
IBM WebSphere Application Server
JUnit
Mercurial
P4
Stash
Vagrant
Visual Studio
Wipro Cloud Studio

API Availability

API Availability

Has API

Pricing Information

Pricing not provided

Pricing Information

Pricing not provided

Supported Platforms

SaaS

Supported Platforms

SaaS
Windows
Mac
Linux

Customer Service / Support

Web-Based Support

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Training Options

Documentation Hub
Online Training

Training Options

Documentation Hub
Online Training
On-Site Training

Company Facts

Organization Name

Syntheticus

Date Founded

2020

Company Location

Switzerland

Company Website

syntheticus.ai/

Company Facts

Organization Name

GenRocket

Date Founded

2012

Company Location

United States

Company Website

www.genrocket.com/enterprise-features/

Categories and Features

Categories and Features

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