Mostly AI
Contact SalesSynthetic data generation platform for secure AI development
By Tanmay Verma, Founder · Last verified 28 May 2026
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Added 7d ago
76/100Safe BetSynthetic data generation platform for secure AI development
By Tanmay Verma, Founder · Last verified 28 May 2026
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A strong choice for organizations needing privacy-safe synthetic data at scale. The open-source SDK and support for Databricks are key differentiators, but pricing details are absent, so enterprise buyers should expect custom quotes.
Last verified: May 2026
MOSTLY AI is a compelling synthetic data platform for enterprises that need to balance data access with privacy compliance. It excels in scenarios like generating synthetic data for AI/ML training, test data for QA, and simulated data for what-if analysis. The open-source Synthetic Data SDK under Apache v2 is a standout, allowing full control in local environments. The AI Assistant for natural language queries adds a layer of accessibility for non-technical users. However, the platform likely targets larger organizations given the enterprise focus (Kubernetes, OpenShift), and pricing is not listed, which may deter small teams. Compared to alternatives like Gretel or Tonic.ai, MOSTLY AI emphasizes speed (100x faster training) and built-in differential privacy. Real-world caveats: users may need to invest in infrastructure for self-hosted deployments, and the platform's full value requires adopting the entire ecosystem (SDK + platform UI). If you need a turnkey, fully managed SaaS, this might not be the best fit.
Skip Mostly AI if Skip MOSTLY AI if you need a fully free synthetic data tool or require generating image, audio, or video data.
Third-party HN post unrelated to MOSTLY AI — ignored.
Blog post comparing SDV and MOSTLY AI SDK on foreign key generation — older than 90 days.
How likely is Mostly AI to still be operational in 12 months? Based on 6 signals including funding, development activity, and platform risk.
MOSTLY AI provides a data intelligence platform for generating synthetic data, mock data, and simulated data to enable secure AI/ML development, testing, and data sharing. It is designed for data scientists, developers, and enterprises needing privacy-safe, high-fidelity datasets. The platform includes an AI Assistant for natural-language data analysis, a Synthetic Data SDK for local generation, and supports integrations like Databricks. Key features include differential privacy, 100x faster training with TabularARGN, and exportable generators. It positions itself as a comprehensive solution for agentic data science, differentiating with open-source SDK and enterprise-grade deployment on Kubernetes or OpenShift.
Tell us what you want to build — we'll match the AI tools that fit your goal, budget & existing stack.
Concrete scenarios for the personas Mostly AI actually fits — and what changes day-one when you adopt it.
Needs to share customer transaction data with a third-party analytics vendor without exposing PII.
Outcome: Uses the Synthetic Data SDK to train a generator on real transactions, generates a privacy-safe synthetic dataset, and shares it—complying with regulations while preserving data utility.
Needs realistic test data for a new feature but has no access to production data.
Outcome: Uses the platform's Mock Data feature to generate structured relational data that mimics production schemas, enabling faster and safer testing cycles.
Wants to analyze patient data trends but cannot access raw data due to HIPAA constraints.
Outcome: Connects to a synthetic copy of the patient database via the AI Assistant, runs natural-language queries, and derives insights without violating privacy.
Pricing is contact-only with no public tiers, making it inaccessible for individual or small-team exploration. The platform focuses on tabular data; unstructured data like images or audio is not supported. Some advanced features (e.g., multi-table synthesis) may require understanding of relational data modeling.
The company stage and team size where Mostly AI's pricing actually pencils out — and where peers do it cheaper.
MOSTLY AI's pricing is contact-only, likely targeting enterprise budgets. For smaller teams or individual developers, open-source alternatives like Gretel or YData offer free tiers or usage-based pricing. MOSTLY AI's value proposition lies in privacy compliance and scalability for large enterprises.
How long it actually takes to get something useful out of Mostly AI — broken out by persona, not the marketing-page minute.
For a data scientist: minutes to install the open-source SDK (`pip install mostlyai`) and train a first generator on a dataset. For the full platform: a demo request and deployment on Kubernetes/OpenShift may take a few hours to days depending on environment.
How to bring data in from common predecessors and how to get it back out — written for the switcher, not the buyer.
If you’d like to recreate this experiment yourself, follow along in the companion notebook.
If you’d like to recreate this experiment yourself, follow along in the companion notebook.
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Blog on simplifying synthetic data workflows using AI assistant — older than 90 days.
Last calculated: May 2026
Synthetic data workflows have traditionally required a mix of engineering effort, platform knowledge, and careful coordination across tools. You upload a
Durable execution platform for crash-safe AI agents and workflows.
