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MOSTLY Generate

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About MOSTLY Generate

MOSTLY Generate is a data generation software from MOSTLY AI that supports synthetic data creation. It combines advanced machine learning algorithms, customizable data generation templates, and data privacy features so organizations can create realistic datasets for testing and analysis. The software is designed to produce data that mimics real-world datasets while preserving sensitive information. Users can generate varied data types, ensuring flexibility for different use cases. Key capabilities: customizable templates machine learning algorithms data privacy compliance varied data type generation user-friendly interface Best for: data scientists and analysts that need realistic datasets for testing and development.

MOSTLY Generate Details

Vendor
MOSTLY AI
Year Launched
2017
Location
Vienna, Austria
Deployment
cloud
Training Options
documentation
Countries Served
All Countries
Languages
English, Spanish, French, German, Italian, Portuguese, Dutch, Japanese, Chinese
Users
Data Scientists, AI/ML Developers, Data Engineers, Privacy and Governance Professionals, Quality Assurance (QA) Engineers, Business Analysts, Compliance Officers, Software Testers, Innovation and Digital Transformation Leaders, Product Managers
Industries Served
Financial Services (Banking, Insurance, Payments), Healthcare and Pharmaceuticals, Telecommunications, Public Sector and Government, Retail and E-commerce, Technology, Transportation and Mobility, Energy and Utilities, Education, Startups and Research Institutions
Tags
Data Management, Data Generation, AI, Machine Learning, MOSTLY AI

MOSTLY Generate's In-App Market Place

Does MOSTLY Generate have an in-app market place?

Yes

How many Mini-Apps in the marketplace?

1

Mini Apps

N/A

Pricing Options

Free trial
Free version
Request a quote
Promo Offer

Accepted Payment Currencies

USD ($), EUR (€), GBP (£), AUD (A$), CAD (C$), JPY (¥), CNY (¥), INR (₹), RUB (₽), BRL (R$)

Pros & Cons

  • Privacy-safe synthetic data: Enables secure data sharing and analysis without exposing sensitive information
  • Agentic AI assistant: Allows natural language queries and Python-based analysis for intuitive data exploration
  • Enterprise-ready deployment: Supports Kubernetes, OpenShift, and VM environments for scalable integration
  • Open-source SDK: Offers local synthetic data generation with full control and no data upload required
  • Advanced model architecture: TabularARGN delivers high-fidelity synthetic data with differential privacy and fast training
  • Collaboration tools: Facilitates team-based asset management and role-based access control
  • Flexible data ingestion: Accepts complex tabular and textual datasets without requiring cleanup
  • Designed for AI/ML workflows: Accelerates development and testing with synthetic data tailored to model needs
  • Requires technical expertise: Python SDK and AI assistant may have a learning curve for non-technical users
  • Focused on synthetic data: May not suit teams needing broader data engineering or orchestration capabilities
  • Limited visibility in mainstream enterprise stacks: Adoption may be lower compared to larger AI platforms
  • Performance dependent on local resources: Synthetic data generation speed and scale rely on user infrastructure

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