Mostly AI
Claim this toolUnlock data access and insights with privacy-safe synthetic data and AI-powered analysis.
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17 reviews trackedThe Bottom Line
Entry price
Free plan available, paid tiers above
Biggest pro
Ensures privacy compliance by generating anonymous synthetic data.
Biggest con
Requires understanding of generative AI concepts for optimal use.
TL;DR - Mostly AI
- Generates high-fidelity, privacy-safe synthetic data for secure sharing and AI training.
- Provides AI-powered analysis of both real and synthetic data using natural language.
- Offers mock and simulated data generation for robust testing, prototyping, and scenario modeling.
Pricing: Free plan available
Best for: Growing teams
4.5/5 across review platforms
What is Mostly AI?
The MOSTLY AI Data Intelligence Platform provides a comprehensive solution for organizations to access, analyze, and share data securely. It enables users to generate high-quality, privacy-safe synthetic data that mimics real data without exposing sensitive information, facilitating safe collaboration, model training, and data sharing. The platform also allows for the analysis of real-world production data, surfacing insights directly from enterprise systems.
Designed for individuals, teams, and enterprise organizations, the platform accelerates AI innovation, streamlines workflows, and drives smarter decision-making at scale. It offers tools for creating mock data for testing and prototyping, and simulated data for modeling edge cases and future scenarios. With agentic data science at its core, it empowers users to leverage AI-powered insights through natural language queries and Python code generation.
Available on: Web
Pros & Cons
Pros
- Ensures privacy compliance by generating anonymous synthetic data.
- Accelerates development and testing cycles with on-demand, realistic data.
- Improves test coverage and quality by providing diverse and representative test scenarios.
- Maintains referential integrity across multi-table datasets.
- Allows data to remain within the user's secure environment for local generation.
Cons
- Requires understanding of generative AI concepts for optimal use.
- The quality of synthetic data is highly dependent on the accuracy of the underlying models.
- Initial setup and integration into existing data pipelines may require technical expertise.
Ratings Across the Web
4.5(17 reviews)
Ratings aggregated from independent review platforms. Learn more
Preview
Key Features
Real-World Data AnalysisAI-Generated Mock DataHigh-Fidelity Synthetic Data GenerationControlled Data SimulationAI Assistant for Natural Language Data AnalysisTeam Collaboration and Asset ManagementEnterprise-Ready Deployment (Kubernetes, OpenShift)Synthetic Data SDK (Open Source)
Pricing Plans
Pricing checked Jul 12, 2026
Free
Free forever
- 1 active chat
- 2 credits per day (max. 25 per month)
- SaaS Platform Usage
- Email Support
Marketplace
$3,000 / month
- 1 Platform Installation
- Unlimited usage
- Cloud Marketplace Platform Usage
- Dedicated Support
- API & Python SDK
- SLAs
- User Groups
- SSO*
Enterprise
Contact us
- Custom number of Platform Installations
- Unlimited usage
- Custom Deployment Platform Usage
- Dedicated Support
- API & Python SDK
- SLAs
- User Groups
- SSO*
Reviews
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4.5/5
Across 17 verified user reviews on G2
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Mostly AI FAQ
How does MOSTLY AI ensure the privacy of sensitive information when generating synthetic data?
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.
Can the Synthetic Data SDK be used independently of the MOSTLY AI Data Intelligence Platform?
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.
What types of data can be used to generate mock data, and how does it differ from traditional mock data tools?
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.
How does the AI Assistant facilitate data analysis for users who may not be expert data scientists?
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.
In what deployment environments can the MOSTLY AI Data Intelligence Platform be run?
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