uses state of the art deep learning generative models

to create realistic synthetic datasets. They possess the same statistical properties and characteristics of the original privacy-sensitive dataset, without the confidential and sensitive data elements. data factory
1. Train will learn the data structure and behaviors of your original input dataset.

2. Generate

Create synthetic data instances that will be different, but indistinguishable, from the original data points.

3. Share

Distribute the synthetic version of your data without disclosing any sensitive information. can run on the cloud or be deployed into existing infrastructures.

The software can be easily integrated into existing data pipelines or deployed as a stand-alone solution according to the customer’s need.

Software as a service (SAAS) is available as an online platform, where data can be securely uploaded through a transfer API for storage on HDFS nodes to ensure scalability to large datasets.

Local deployment

Reduce any privacy-related concerns that companies may have regarding uploading their data on a secured cloud by directly installing Intuite.AI on your premises.