Betterdata
Enterprise synthetic data platform for generating privacy-preserving tabular, relational and sequential data for AI/ML, testing and secure data sharing.
At a Glance
About Betterdata
Betterdata is a Singapore-based company, founded in 2021 by Dr. Uzair Javaid, that builds an enterprise synthetic data platform for data generation, privacy protection and analysis. It produces tabular, relational and sequential synthetic datasets intended for AI/ML development, analytics, system testing and secure data sharing in regulated environments.
What It Is
Betterdata is synthetic data infrastructure for enterprises and governments. It transforms sensitive or slow-moving real data into synthetic datasets that, according to the company, preserve the structure and utility of the original data without exposing personally identifiable information. The company cites proprietary technologies such as ARF and IRG.
How Generation and Privacy Work
The site describes a multi-model engine that combines a Tabular Foundation Model (TFM), deep learning (GANs), tree-based models (SPN, ARF) and transformer-based models (LLMs). Privacy protection relies on Differential Privacy guarantees, PII redaction and audits intended to produce compliant datasets. Users can also generate and augment data to train AI/ML models with more diverse and balanced training data.
Deployment Model
Betterdata states it deploys from one VM to thousands using a single CIS-hardened package, on-premise, air-gapped, or on any cloud provider.
Use Cases
Listed use cases include anti-money laundering, GDPR and HIPAA compliance, prototyping AI/ML products, insurance claims forecasting, algorithmic trading backtesting, customer analytics and CLV, and Basel III/IV capital modeling. The company's case studies describe work with a government agency, a bank, and enterprises; these are vendor-published claims.
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Pricing
Contact sales
Enterprise synthetic data platform; pricing available via sales contact.
Capabilities
Key Features
- Multi-model synthetic data engine (TFM, GANs, SPN, ARF, LLMs)
- Tabular, relational and sequential data synthesis
- Differential Privacy guarantees
- PII redaction and regulatory-grade audits
- On-premise, air-gapped and cloud deployment
- CIS-hardened single package deployment
- Synthetic data augmentation for AI/ML training
- Secure data sharing
Demo Video

