MOSTLY AI provides a platform that generates fully anonymous synthetic data using optimized Generative AI models, enabling organizations to share sensitive data while ensuring compliance with privacy regulations like GDPR and CCPA. This technology addresses the challenge of restricted data access for AI/ML development and analytics, allowing teams to derive insights and improve model performance without compromising data privacy.
Funding
$31.2M raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
Founders
Product
Problem
Organizations face challenges in sharing sensitive data for AI/ML development and analytics due to privacy regulations like GDPR and CCPA, which restrict data access and hinder innovation. Traditional data anonymization techniques often fall short, either failing to adequately protect privacy or distorting the data to the point of being unusable.
Solution
MOSTLY AI provides a platform that leverages Generative AI to create fully anonymous synthetic data, enabling organizations to share and explore data assets without compromising privacy. The platform's GenAI models learn the statistical patterns and relationships within the original data to generate highly realistic synthetic data. This synthetic data mirrors the structure and insights of the real data without containing any actual identifiable information, allowing teams to derive insights, improve model performance, and accelerate AI/ML development while adhering to privacy regulations. The platform also offers a natural language interface, allowing users to explore data and extract insights without coding skills.
Target Audience
The primary target audience includes data scientists, data analytics teams, AI/ML developers, and enterprise organizations seeking to unlock the value of their data while adhering to stringent privacy requirements.
Features
- GenAI-powered data exploration and analysis through a natural language interface, accessible to users without specialized expertise
- Creation of fully anonymous synthetic data from original data, ensuring compliance with privacy regulations like GDPR and CCPA
- Optimized GenAI models for tabular data, resulting in high performance and scalability
- Support for multi-variate time series data and multi-table relational databases
- Option to train synthetic data generators with or without differential privacy (DP) guarantees, providing flexibility based on privacy needs
- Integration with Databricks through a Solution Accelerator, simplifying the implementation of synthetic data generation within the Databricks Intelligence Platform
- Ability to fine-tune pre-trained language models (LLMs) with proprietary text data to create synthetic text
- Capability to use Generators as Universal Prediction Models to infer missing values in datasets
- Option to generate synthetic data with a fairness objective, ensuring that the distribution of the target column is statistically independent of sensitive columns
- Python client for managing data workflows out of any Python environment