gretel

JSON twin: https://www.healthaidb.com/software/gretel.json

Company Name

Gretel

Product URL

https://gretel.ai/solutions/healthcare

Company URL

https://gretel.ai

Categories

Summary

Gretel provides enterprise-grade synthetic data generation and augmentation tools (Navigator, Data Designer, Safe Synthetics, APIs/SDKs) to create privacy-preserving datasets for ML training, testing, and safe data sharing.

Description

Gretel is a synthetic data platform offering GUI and programmatic tools (Gretel Navigator, Data Designer, Safe Synthetics, SDKs and REST APIs) to generate, edit, augment, and anonymize tabular and structured datasets at scale. It supports real-time inference, differential-privacy options, enterprise deployment patterns (cloud, hybrid), documentation and examples for ML training, model evaluation, RAG testing, and safe healthcare data sharing.

Api Available

yes

Certifications

Company Founding

2019

Company Offices

—

Compliance

Customers

Data Residency

Managed cloud with option for private cloud / bring-your-own-cloud deployment (region selection via customer cloud)

Data Standards

Deployment Model

Features

Id

P0671

Integration Partners

Integrations

Languages Supported

Last Updated

2025-09-07

License

proprietary (commercial)

Links

Market Segment

Optional Modules

Os Platforms

Pricing Details

public docs show console/API and enterprise plans; no public list prices — contact vendor for pricing and trials

Pricing Model

enterprise_quote

Privacy Features

Ratings

Regions Available

Release Year

2019

Security Features

Specialties

Support Channels

System Requirements

Target Users

Training Options

Type

product

User Reviews

Version

1.0

Canonical JSON

{
  "company_name": "Gretel",
  "company_url": "https://gretel.ai",
  "company_offices": [],
  "company_founding": "2019",
  "product_url": "https://gretel.ai/solutions/healthcare",
  "categories": [
    "data privacy",
    "synthetic data",
    "AI/ML",
    "developer tools",
    "analytics"
  ],
  "market_segment": [
    "enterprise",
    "smb",
    "developer"
  ],
  "links": [
    "https://gretel.ai",
    "https://gretel.ai/solutions/healthcare",
    "https://docs.gretel.ai",
    "https://docs.gretel.ai/create-synthetic-data/safe-synthetics",
    "https://gretel.ai/security",
    "https://gretel.ai/contact",
    "https://console.gretel.ai",
    "https://www.g2.com/products/gretel/reviews",
    "https://www.capterra.com/p/268653/Gretel/",
    "https://techcrunch.com/2025/03/19/nvidia-reportedly-acquires-synthetic-data-startup-gretel/"
  ],
  "summary": "Gretel provides enterprise-grade synthetic data generation and augmentation tools (Navigator, Data Designer, Safe Synthetics, APIs/SDKs) to create privacy-preserving datasets for ML training, testing, and safe data sharing.",
  "description": "Gretel is a synthetic data platform offering GUI and programmatic tools (Gretel Navigator, Data Designer, Safe Synthetics, SDKs and REST APIs) to generate, edit, augment, and anonymize tabular and structured datasets at scale. It supports real-time inference, differential-privacy options, enterprise deployment patterns (cloud, hybrid), documentation and examples for ML training, model evaluation, RAG testing, and safe healthcare data sharing.",
  "target_users": [
    "data scientists",
    "machine learning engineers",
    "data engineers",
    "privacy engineers/data stewards",
    "analytics teams",
    "developers",
    "product managers",
    "clinical researchers"
  ],
  "specialties": [
    "healthcare data / EHR de-identification",
    "finance",
    "AI/data platform development",
    "NLP / RAG evaluation",
    "ML model training and testing"
  ],
  "regions_available": [
    "United States",
    "Canada",
    "United Kingdom",
    "European Union",
    "Australia",
    "Global"
  ],
  "languages_supported": [
    "English"
  ],
  "pricing_model": "enterprise_quote",
  "pricing_details": "public docs show console/API and enterprise plans; no public list prices — contact vendor for pricing and trials",
  "license": "proprietary (commercial)",
  "deployment_model": [
    "managed cloud (SaaS)",
    "private cloud / self-hosted (BYO cloud)"
  ],
  "os_platforms": [
    "Web (Gretel Console)",
    "Linux (SDK/CLI)",
    "macOS (SDK/CLI)",
    "Windows (SDK/CLI)"
  ],
  "features": [
    "Synthetic EHR / synthetic healthcare record generation",
    "Differential privacy-enabled generation (tunable privacy filters)",
    "Gretel Data Designer (schema-driven data generation)",
    "Safe Synthetics (tabular and text synthetic engines)",
    "SDKs and CLI (Python client and REST API)",
    "Connectors for object storage, databases, and warehouses",
    "Seeding and structured output generation",
    "Privacy & synthetic quality evaluation reports",
    "Transform workflows for data preprocessing",
    "Fine-tuning for tabular and text models",
    "Model suites for different data types",
    "Console for project management and job monitoring",
    "Blueprints and use-case templates for healthcare",
    "Tools to augment/ balance datasets and simulate rare conditions",
    "Support for generating synthetic conversations / clinical text"
  ],
  "optional_modules": [
    "Gretel Data Designer",
    "Gretel Safe Synthetics",
    "Gretel Console (Managed UI)",
    "Model Suites / Fine-tuning modules",
    "Privacy evaluation & benchmarking reports"
  ],
  "integrations": [
    "Amazon S3",
    "Google Cloud Storage",
    "Azure Blob Storage",
    "Snowflake",
    "BigQuery",
    "Databricks",
    "MySQL",
    "PostgreSQL",
    "MS SQL Server",
    "Oracle Database"
  ],
  "data_standards": [],
  "api_available": "yes",
  "system_requirements": "",
  "compliance": [
    "HIPAA",
    "GDPR"
  ],
  "certifications": [],
  "security_features": [
    "Differential privacy",
    "Tunable privacy filters",
    "Encryption (in transit and at rest)",
    "Role-based access control (RBAC)",
    "Audit logging"
  ],
  "privacy_features": [
    "Differential privacy-based generation",
    "Anonymization / de-identification",
    "Tunable privacy settings",
    "Synthetic data as privacy-preserving alternative to real PHI"
  ],
  "data_residency": "Managed cloud with option for private cloud / bring-your-own-cloud deployment (region selection via customer cloud)",
  "customers": [
    "Illumina",
    "South Australian Health (SA Health)",
    "Athena Intelligence",
    "NVIDIA (acquirer)",
    "Major healthcare institutions (unnamed case study)",
    "Hospitals / Health Systems",
    "Ambulatory practices",
    "Digital health providers"
  ],
  "user_reviews": [
    "The best feature of Gretel is its accessibility and open source.",
    "Gretel makes it really easy to generate artificial datasets with the same characteristics as real data.",
    "Synthetic data from Gretel allowed us to create realistic EHR datasets for demos and testing without exposing PHI.",
    "Gretel's Safe Synthetics and privacy metrics gave us confidence to share datasets across teams.",
    "Worked well for tabular healthcare data generation and rapid prototyping of ML models."
  ],
  "ratings": [
    ""
  ],
  "support_channels": [
    "documentation",
    "email",
    "community",
    "ticketing"
  ],
  "training_options": [
    "documentation",
    "webinars",
    "live_online"
  ],
  "release_year": "2019",
  "integration_partners": [
    "Microsoft (case studies / partnership)",
    "WorkOS",
    "Hugging Face (datasets / ecosystem)",
    "GitHub (open-source repos)",
    "Athena Intelligence",
    "Illumina",
    "South Australian Health (collaboration)"
  ],
  "id": "P0671",
  "slug": "gretel",
  "type": "product",
  "version": "1.0",
  "last_updated": "2025-09-07",
  "links_json": {
    "self": "https://www.healthaidb.com/software/gretel.json"
  }
}