
Unlock data access and insights with privacy-safe synthetic data and AI-powered analysis.
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MOSTLY AI employs advanced generative models and built-in differential privacy to create synthetic datasets that statistically mimic real data without containing any identifiable information from the original dataset. This ensures that the synthetic data is fully anonymous and exempt from data protection regulations, making it safe for sharing and use in non-production environments.
Yes, the Synthetic Data SDK is an open-source project that allows users to generate synthetic data locally within their Python environment. This provides full control over the data, as it never leaves the user's environment. Generated models can then be exported and optionally uploaded to the MOSTLY AI Data Intelligence Platform for further exploration and sharing.
MOSTLY AI's mock data generation uses an LLM-powered approach to create schema-compliant, multi-table datasets that mirror real-world structure and behavior without requiring access to production data. Unlike traditional tools like Faker, which generate obviously synthetic values, or LLMs like ChatGPT, which lack structure, MOSTLY AI's mock data maintains referential integrity and realistic distributions, making it suitable for robust testing and CI/CD pipelines.
The AI Assistant allows users to analyze data using simple natural language queries. It can generate and run Python code based on these queries, making data analysis accessible to a broader audience, from beginners to experts, and enabling them to gain insights from both production and synthetic data without extensive coding knowledge.
The MOSTLY AI Data Intelligence Platform is designed for enterprise-ready deployment and can be run on Kubernetes or OpenShift. This provides scalability and security, allowing organizations to connect to their data within their secure environment and run on their own compute infrastructure.
Source: mostly.ai