Snazhana Uvarova

ZONE3000 is an international IT company founded in 1998. It is among the top ten leaders of the Ukrainian IT industry. We specialize in providing services and services for software product development in the areas of domains, hosting, security certificates, personal e-mail and others.

Since 1998, we have staffed more than 2,000 professionals in six ZONE3000 locations: Kharkiv, Lviv and Dnipro. The company's teams help clients create world-class products and grow their businesses in partnership.

ZONE3000 Kharkiv and Lviv product lines support and develop more than 20 products.

Mostly AI is an AI-based big data analytics platform to comprehend client manners. It lets users follow and manage big data from different bases. It examines and supplies understandings connected to client manners and creates predictive standards by operating deep learning, machine learning, and artificial intelligence technologies. By operating a synthetic data engine it lets users simulate data, develop marks, and comprehend the deviations in the data using deep neural networks.

Main Facts

Synthetic data is fake data, but not accidental: basic AI operates artificial intelligence to reach a high grade of loyalty in its client databases. His datasets look as natural as the actual customer data of the company, with the identical quantity of facts, but without the actual individual data issues.

Mostly AI was established in Vienna in 2017, and a year later the General Data Protection Regulation (GDPR) was presented in the EU. This need for solitude resolutions and the simultaneous upgrade in machine learning has made considerable growth for synthetic data. Gartner expects that by 2024, 60% of the data used to create AI and analytics assignments will be developed synthetically.

While the startup has a stable technological base, it supports equally in the commercialization of its technology and in the company worth, it may count to its clients. Essentially, AI is guiding the course in this unique and fast-growing field both in times of client deployment and knowledge.

MOSTLY AI sees the significant possibility of operating synthetic data in software testing. To keep these use issues, it is essential to create synthetic data known not just to data scientists but even to software makers and rate testers.