Synthesized named a Gartner Cool Vendor 2021

AI Governance and Responsible AI for 2021
Synthesized uses AI and GANs to generate synthetic data, and systematically identifies and mitigates bias in the resulting dataset. We address issues concerning both AI-related privacy and bias, while retaining the same statistical power in the model’s original dataset.

What is a Cool Vendor?

According to Gartner, the three elements of a Cool Vendor are defined as:

Innovative

Enables users to do things they couldn’t do before

Impactful

Has or will have a business impact, not just technology for its own sake

Intriguing

Caught Gartner’s interest during the past six months

By 2024, 60% of the data used for the development of AI and analytics solutions will be synthetically generated.

— Gartner

What Gartner says:

Organisations that are coming under increasing security to ensure their AI models are performing within legal and ethical bounds when it comes to bias and fairness should consider Synthesized.

With Synthesized you can:

Detect and mitigate bias automatically.
Automatic detection of hidden biases across protected attributes such as age, gender, race
Bias-free and high quality synthetic data

What Gartner says:

Data and analytics leaders who need a collaboration on AI models internally and with other organizations but are inhibited to do so because of privacy and data leakage concerns should consider Synthesized.

With Synthesized you can:

Collaborate risk-free.
Shareable high-quality data products for model development and training
Compliant by design
Model performance meets or exceeds that of original data

What Gartner says:

Organisations that require both high-quality data assets and need granular control over their data products should consider Synthesized.

With Synthesized you can:

Increase model performance with comprehensive data science tools and high quality data products.
Reshape and manipulate data
Impute missing values
Create unlimited new volumes of data in minutes

Gartner recommends examining synthetic data as a means for creating AI that is compliant, fair and bias free to conform to today’s growing legal and ethical demands