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NeMo Safe Synthesizer

NeMo Safe Synthesizer creates private, safe versions of sensitive tabular datasets -- entirely synthetic data with no one-to-one mapping to your original records. It uses LLM fine-tuning with optional differential privacy to produce high-quality datasets that preserve the statistical properties and utility of your data for downstream AI tasks while ensuring privacy compliance and protecting sensitive information.

Key Features

  • Privacy-first synthetic data -- PII detection and replacement, optional differential privacy while fine-tuning via Opacus
  • LLM fine-tuning -- LoRA fine-tuning optimized for tabular data, including numeric, categorical, and text columns
  • Fast inference -- vLLM-powered generation with optional structured output enforcement
  • Comprehensive evaluation -- Privacy and quality metrics in an in-depth HTML report
  • Flexible interfaces -- CLI for scripting, Python SDK for programmatic workflows, YAML configuration

System Requirements

NeMo Safe Synthesizer requires a Linux machine with an NVIDIA GPU (A100 80GB+ recommended) and CUDA 12.9+ to run the training and generation pipeline. macOS, Windows, and Apple Silicon are not supported for pipeline execution. A CPU-only install is available for development and configuration validation -- see Getting Started.

Next Steps

  • Getting Started

    Install the package, set up your environment, and run your first synthetic data pipeline in minutes.

    Getting Started

  • Product Overview

    Learn about the pipeline steps: replace PII, synthesize data, evaluate.

    Product Overview

  • Tutorials

    Follow hands-on tutorials to generate synthetic data.

    Tutorials

  • User Guide

    Configure and run the pipeline via YAML, CLI, SDK, or environment variables.

    User Guide

  • Developer Guide

    Browse the auto-generated API reference and dive into the architecture details.

    Developer Guide

  • Dev Notes

    Read developer blog posts.

    Developer Notes

Telemetry & Privacy

NeMo Safe Synthesizer includes an optional function to share anonymous telemetry data with NVIDIA for product improvement. Data collected is limited to run-level operational metrics (such as final run status, processing time, record and token counts, configuration parameters, top-level quality and privacy scores, base model used, deployment type, and GPU type). No user or device information is collected. This data is used to prioritize product improvements and will be shared in aggregate with the community. It is not used to track any individual user behavior.

You may opt out of telemetry collection at any time. Opting out applies only to data collection by the NeMo Safe Synthesizer library itself. To disable telemetry in a YAML config, set:

emit_telemetry: false

To disable telemetry for one CLI invocation, pass --emit_telemetry false:

safe-synthesizer run --emit_telemetry false --data-source my_data.csv

To disable telemetry for the current shell, set NEMO_TELEMETRY_ENABLED=false (other accepted disabling values: 0, no) in your environment before running:

export NEMO_TELEMETRY_ENABLED=false

Use of third-party endpoints, including NVIDIA Build: NeMo Safe Synthesizer can be configured to use various inference endpoints, including build.nvidia.com (NVIDIA Build). If you choose to use NVIDIA Build or any other third-party endpoint, that endpoint's own terms of service and privacy practices apply independently of this library. Any opt-out you exercise within NeMo Safe Synthesizer does not extend to data collection by your chosen endpoint. NVIDIA Build is intended for evaluation and testing purposes only and may not be used in production environments. Do not submit any confidential information or personal data when using NVIDIA Build.

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License

NeMo Safe Synthesizer is licensed under the Apache License 2.0.