Improve your downstream applications on data sharing, software testing, ML modelling, and by extension, any data-driven task. Expand diversity, increase domain coverage, eliminate bias, and fuel robust, adaptable models for seamless development and production scaling in three simple steps.

Data Ingestion

Automatically ingest any structured data (CSV, JSON, Parquet, Excel, or live DB connectors) and prepare it for model training

Model Training

Choose from a powerful suite of SOTA generative models built for high quality structured data

Data Generation

Generate high-fidelity, privacy-perserving synthetic datasets with quality and privacy assurance reports

A Model for Every Use-Case

Choose from our suite of proprietary state-of-the-art (SOTA) synthetic data generation models, and generate high-quality synthetic data at scale fit for enterprise AI/ML applications and other data-intensive use cases.

Tabular SOTA

TabTreeFormer

Our best-in-class model for
accuracy + performance

ARF

CPU-based for lightweight,
low compute environments

CTAB-GAN-DP

For privacy focused
applications

Tabula

For low-latency and highest
accuracy generation

Relational SOTA

IRG-GAN

Generate full database schemas
with referential integrity

SPN

CPU-efficient for lightweight and
low compute environments

Time Series

Fractal-TSG

Support structured,
timestamped data

TS-V0

Support regular, structured,
timestamped data

TS-V1

Support irregular (event-driven)
structured, timestamped data

Learn more about all of our SOTA models

Built for effortless synthetic data generation

Promptable Models

For non-technical users to generate synthetic data via simple natural language prompts using our fine-tuned foundation model.

Non-Promptable Models

For power users working with structured data allowing for more controlled training and generation of synthetic datasets that align closely with real-world data patterns.

Supporting Multiple Data Modalities

We adapt to your data availability. If you have no data, use our pre-trained Tabular Foundation Model (TFM) trained on 1B+ records. For limited data, fine-tune efficiently with our LLM and GAN-based models. With rich datasets, unlock full-scale training for optimal performance. Flexible, powerful, and built for any scenario.

Tabular Data

Relational Data

Time-Series Data

Text-in-Table

Protect Sensitive Customer Information

Enterprise-grade synthetic data with guaranteed privacy compliance, engineered to outperform real data while eliminating all PII risks. The only solution that delivers both regulatory safety and superior ML performance.

Integrated Differential Privacy

Advanced Anonymization Techniques

Versioning and Dataset Locking

CIS Hardened Packages

Precise RBAC Permissions

Frequently Asked Questions (FAQ)

We're here to help. Can't find the answer to your question?
Contact us here.

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