Synthetic Data Generator | Homeland Security
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Synthetic Data Generator

  • Betterdata (Singapore) is leveraging its Large Synthetic Model capabilities to generate synthetic data that is statistically accurate when real data is unavailable or low in volume, while enhancing data auditing using differential privacy. The solution supports tabular, sequential, relational and text data modalities. (Initial award date September 2024) - Currently in Phase 1 
  • Datacebo (Boston, MA) is creating AI-generated synthetic data using its Synthetic Data Vault E platform which lets developers easily build, deploy and manage sophisticated generative AI models for enterprise-grade applications when real data is limited or unavailable. (Initial award date September 2024) - Currently in Phase 1 
  • MOSTLY AI (Vienna, Austria) is using its generative AI Platform to create highly accurate and private tabular synthetic data to support model training, analytics and testing use cases. In addition, the platform has unique capabilities around generating fair synthetic data to combat bias in synthetic data generation. (Initial award date September 2024) - Currently in Phase 1 
  • Rockfish Data (San Ramon, CA) developed a high fidelity and privacy-preserving generative data platform that automatically adapts to diverse operational datasets and enables flexible generation for myriad use cases. Based on foundational research at Carnegie Mellon University, the Rockfish platform helps customers accelerate their AI transformation and improve the security, resilience and innovation in operations. (Initial award date September 2024) - Currently in Phase 1 
Last Updated: 12/10/2024
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