Public Sector

Generate safe synthetic
government data
at scale

Enable public sector innovation while safeguarding citizen and national privacy with synthetic data for government data analytics, ML, and software development.

Synthetic government data with limitless possibilities

Generate Safe Synthetic Data for Government Data Analytics, ML, and Software Development.

  • Safe Government Data Analytics

    Utilize privacy-first synthetic data to conduct Safe government data analytics within federal agencies, ensuring that sensitive and classified information remains protected.

  • Data-Driven Decisions

    Make informed decisions and enhance strategic planning without exposing actual data to potential vulnerabilities or breaches.

  • Private Sector Collaboration

    Harness the power of privacy-first synthetic data to safely share anonymized information with external research partners or contractors.

  • Software Development

    Unlock data access for non-production environments increasing development cycles and productivity while eliminating sensitive data exposure.

Synthesize Training Data for LLMs and Conversational AI

  • Enhanced Language Models for Intelligence Analysis

    Train large language models (LLMs) using synthetic data to provide enhanced assistance in analyzing and interpreting vast amounts of unstructured data, deriving actionable insights securely without utilizing sensitive or classified information.

  • LLM-Powered Public Services

    Deliver cutting-edge government services through LLMs, guaranteeing that citizens receive the highest quality of care and support from government applications.

Boost Model Robustness with Synthetic Data

  • AI readiness

    Implement AI with safe, high-quality training data across public and private sectors to improve prediction models for both known and unknown threats

  • Government Operation

    Improve model robustness across mission critical mandates: from natural disasters and threat models to fraud detection and more.

The Government Data Challenge

Data challenges in Government

Government agencies are rapidly integrating new data-driven applications and AI, ushered by rapidly evolving technologies and changing adversarial risks. However, working with sensitive government data assets poses unique challenges relating to data privacy.
  • Safeguarding government data

    Multiple data classifications, personnel clearance levels, and classified networks present significant challenges for government data sharing.

  • Multiple secure clouds

    Government clouds are complex with multiple cleared and uncleared environments and rules for cross-environment data transfer.

  • AI readiness

    With a global race for AI dominance, governments need to rapidly build AI training datasets to maintain tactical advantage.


Driving Government innovation with synthetic data

Synthetic data accelerates government innovation and collaboration while protecting citizen and national privacy. By generating artificial records that contain critical insights without exposing any actual sensitive information, synthetic data removes privacy risks.

This allows civil and defense agencies to rapidly share datasets across departments, cloud environments, classified networks, clearance levels, and with external partners. Governments also leverage synthetic data to augment their existing AI training datasets and anonymize sensitive insights in order to accelerate the adoption of AI applications.

Gretel Console
Key Benefits

Why synthetic data for government data analytics, ML, and software development?

  • Quality government data at scale

    Backed by multiple generative AI models and proven across government agencies, scale your data without compromising on quality or privacy.

  • Mitigate risks

    Backed by differential privacy—complete with mathematical guarantees, ensure safe data sharing across classified networks, clearance-levels, and partners.

  • Power mission-critical applications

    Synthetic data makes sensitive data assets safe and better so agencies can quickly operationalize data for mission-critical outcomes.

Public sector resources

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