Mostly AI

What is Mostly AI?

Founded in Vienna, Austria in 2017 by data scientists Michael Platzer, Klaudius Kalcher, and Roland Boubela, Mostly AI specializes in AI-generated synthetic data. Its services include generating high-quality synthetic data, ensuring data privacy and security, providing professional training, supporting AI and machine learning model development, and enabling safe cross-border data sharing.

The company’s platform, GenAI, lets users explore and share tabular data, helps make AI and ML models fairer and less biased, and supports self-service analytics. Mostly AI’s mission is to change how companies handle data by promoting smart, safe synthetic data.

Why was it created?

The founders saw the potential of AI for generating structured business data and synthetic data, and were inspired by the data anonymization challenges companies faced, particularly with GDPR coming into effect in 2018. Their goal is to help organizations use safe synthetic data ethically and to empower everyone with data.

What is Mostly AI used for?

• Secure data sharing, including across borders
• Developing AI and ML models
• Self-service analytics
• Testing and quality assurance (QA)

Who is Mostly AI for?

The tool serves AI/ML developers, data scientists, software developers, QA testers, data analysts, data engineers, and product developers — essentially anyone involved in synthetic data generation or software testing.

How to get started

1. Sign up for free on the Mostly AI platform, or contact the sales team for a tailored demo.
2. Generate up to 100,000 rows of synthetic data per day at no cost.
3. Experiment with the provided sample datasets, or upload your own datasets to create synthetic versions.
4. Use professional services and training if you need guidance.

The platform’s AI-powered technology generates high-quality, privacy-safe synthetic datasets. You can address bias in training datasets using its algorithms to improve fairness in AI/ML models. Useful features include natural language interfaces for exploring data, a Python client for data workflows, and the ability to create tabular data from scratch or enrich existing datasets — all while keeping data private and secure.