AI Synthetic Data platforms create artificial datasets for training and testing machine learning models. These tools generate realistic, privacy-compliant data while maintaining statistical properties and relationships of real-world data.
27 verified AI-first sites in Synthetic Data.
Data synthesis and transformation platform. Features automated data generation, privacy preservation, and bias detection. Includes data quality assessment and compliance tools. Specializes in enterprise data operations.
Pricing: Start-up: $2k/month. Enterprise: Custom pricing.
Database subsetting and synthetic data platform. Features intelligent data generation, automated PII detection, and referential integrity preservation. Includes developer-friendly APIs and enterprise security controls. Specializes in test data management.
Pricing: Team: Custom pricing. Enterprise: Contact for solutions.
SAS synthetic data platform (formerly Hazy, acquired November 2024). Low-code generation of high-fidelity tabular and structured data with statistical validation, privacy controls, and connectors to Databricks, Snowflake, Oracle, and BigQuery.
Pricing: Contact SAS for pricing.
GenAI-powered synthetic data platform that generates high-quality and compliant data samples at scale. Features automated data generation, privacy compliance tools, and integration with major AI platforms for training and testing purposes.
Pricing: Custom pricing based on data volume and use case.
Synthetic data platform combining machine learning generation with rule-based data creation for comprehensive test data solutions. Features AI-generated synthetic data preserving statistical properties of original datasets. Includes rule-based synthetic data generation for custom data patterns and constraints. Offers data masking and anonymization capabilities for privacy-preserving test data. Supports time-series data generation with realistic temporal patterns. Features test data management tools with subsetting and sampling capabilities. Includes integration capabilities with data pipelines and testing frameworks. Particularly valuable for organizations requiring privacy-compliant test data while maintaining data utility. Provides comprehensive synthetic data platform with AI-powered generation and privacy protection.
Pricing: Contact for pricing.
Hyderabad-based synthetic data platform for development, analytics, and ML training. Generates production-like tabular data with GDPR, HIPAA, DPDP Act 2023, and RBI-oriented privacy controls, including UPI and fraud-pattern datasets for Indian finance. Also sells crop-disease, weather, and soil datasets for agritech computer vision and forecasting.
Pricing: Contact for pricing.
No-code synthetic data generation platform enabling fast creation of realistic datasets without requiring real data. Features intuitive interface for describing data requirements and generating synthetic datasets. Includes CSV upload capabilities for generating synthetic data based on existing data structures. Offers privacy-first approach with zero real data storage and complete data isolation. Features realistic data generation maintaining statistical properties and data relationships. Supports multiple data formats with customizable generation parameters. Includes quick dataset creation for testing, demos, and development purposes. Particularly valuable for developers and teams needing rapid synthetic data generation without technical complexity. Provides user-friendly synthetic data platform with privacy-focused design.
Pricing: Contact for pricing.
Enterprise synthetic data platform with programmatic generation. Features multi-model engine including GANs, transformers, and tabular foundation models for tabular, relational, and time-series data. Includes differential privacy guarantees, PII redaction, and regulatory-grade audits for GDPR and HIPAA compliance. Supports on-premise, air-gapped, and cloud deployment. Trusted by Tier 1 banks, Fortune 500 enterprises, and government agencies. Particularly valuable for financial services, fraud detection, and privacy-compliant ML training.
Pricing: Enterprise pricing. Contact for solutions.
Enterprise software for generative relational models of multi-table databases, from the makers of the Synthetic Data Vault. SDV 2.0 trains a model of an organization's connected tables inside their environment, then generates synthetic databases for software testing, AI training, and scenario simulation. SDV Community is a widely adopted Python library with 18M+ downloads; Enterprise is an SDK with self-service pricing from $500/month.
Pricing: SDV Community: Free. SDV Enterprise: from $500/month.
Healthcare data platform offering synthetic data generation for privacy-safe analytics and research collaboration. Enables teams to explore statistically representative data while reducing re-identification risk and compliance exposure.
Pricing: Enterprise and institutional pricing; contact for deployment and licensing.
Synthetic data company providing AI-generated datasets for regulated and data-sensitive environments. Focuses on privacy-preserving data sharing, model development, and secure collaboration across healthcare, finance, and public-sector use cases.
Pricing: Enterprise pricing and project-based plans; contact sales for details.
AI research lab that supplies frontier labs with training data, tasks, and simulated environments for reinforcement learning. Environments cover software engineering, computer use, knowledge work, and scientific research. Published research includes steerable world models, FigmaTrace workflow data, and the MEMTRACK long-term memory benchmark.
Pricing: Contact for project scope and pricing.
Physics-grounded synthetic simulation for physical AI perception. Generates sensor-accurate camera, lidar, radar, and thermal datasets for ADAS, in-cabin monitoring, and defence validation with Euro NCAP-aligned scenario libraries.
Pricing: Enterprise platform and project pricing; contact on site.
Synthetic data and robotics evaluation from Bifrost. Stardust generates photorealistic, pixel-perfect labeled datasets for perception and autonomy across maritime, aerial, geospatial, space, and off-road. Manifold evaluates robot policies on GPU-parallel simulation benchmarks including LIBERO and RoboCasa, used by teams across land, air, sea, and space.
Pricing: Enterprise pricing; book demo on site.
Synthetic data platform for computer vision across SAR, infrared, multispectral, hyperspectral, and RGB sensors. PaaS workflows generate fully labeled imagery for edge cases, rare objects, and regulated domains where real capture is costly or restricted.
Pricing: Platform from about $5K/month; managed SDaaS by project.
NVIDIA Omniverse extension for scalable synthetic 3D data generation. Randomizes scenes, objects, lighting, and sensors to produce labeled datasets for perception, robotics, and digital-twin training pipelines integrated with Isaac and USD workflows.
Pricing: Free with Omniverse; enterprise via NVIDIA AI Enterprise.
Synthetic Data Vault - leading open-source Python ecosystem for tabular, relational, and multi-table synthetic data. SDV, CTGAN, and related libraries for research and production prototypes with free core tooling and optional enterprise add-ons.
Pricing: Open-source core free; enterprise components licensed separately-see SDV.
Privacy-safe synthetic data platform for GDPR-compliant datasets that preserve statistical utility. Used to replace masking, fix class imbalance, and share sandboxed data for AI, analytics, and research without exposing production PII.
Pricing: Contact Clearbox AI for platform and project pricing.
AI Consumer OS that turns research respondents into digital twins and runs surveys, concept tests, and pricing studies on those modeled audiences. Connects existing studies, trackers, and customer records, then answers with cited sources and simulated audience results. Used with consumer brands including L'Oréal, T-Mobile, and Accor; SOC 2 Type II.
Pricing: Demo-led enterprise; see fairgen.ai.
Avatar method for anonymous synthetic tabular data with CNIL-aligned privacy guarantees. SaaS or on-prem generation for healthcare and enterprise AI sharing when real records cannot leave regulated systems.
Pricing: SaaS and on-prem licensing; see octopize.io for plans.
Enterprise synthetic data and safe data-space platform for banking and healthcare. Generates high-fidelity synthetic datasets, validates models, and supports regulated AI programs that cannot use raw production data.
Pricing: Enterprise pricing; contact Dedomena for deployments.
AI synthetic data platform for privacy-safe anonymized datasets. Generates statistically useful synthetic tabular data so teams can innovate and share without exposing production PII.
Pricing: Plans and demos on bluegen.ai.
Synthetic document and tabular data for ML training—realistic filled government, healthcare, and tax forms without real PII. HIPAA-ready and GDPR-safe generation for document-understanding models.
Pricing: Self-serve plans from about $50/month annual; see SymageDocs.
NVIDIA NeMo microservice for privacy-preserving synthetic data (Gretel tech folded into NeMo). Generates differentially private tabular and related datasets for enterprise AI training and evaluation on the NVIDIA stack.
Pricing: NVIDIA AI Enterprise / NeMo microservices; see NVIDIA docs.
Privacy-protected synthetic data for enterprise AI, delivered as a managed service built on its GraphReplica engine. Generates differentially private replicas of tabular, document, and image data that keep keys, joins, and statistical shape intact while replacing PII, PHI, and proprietary entities consistently across files. Each run returns audit-ready leakage and red-team reports aimed at GDPR, CCPA, and HIPAA review, and the company raised a $4M seed in May 2026.
Pricing: Custom pricing; book a demo.
Vienna-based synthetic data engine for Earth observation, built on proprietary generative foundation models. Produces pixel-perfect, auto-labeled satellite, aerial, and drone imagery for any region, sensor, and resolution, from 10m Sentinel-style data to 25cm aerial. Procedural 3D enhancement and scenario simulation support climate, mining, insurance, and infrastructure risk models, and a case study cites 95% less ground-truth data needed.
Pricing: Custom pricing; contact sales.
Synthetic data platform that trains its own generative models on a sample or schema, then produces labeled tabular and time-series data for ML and agent evals. Named engines include RF-Time-GAN, RF-Time-Transformer, RF-Tab-Transformer, and RF-Tab-GAN, with Scenario Studio to inject incidents, drifts, and rare events. Deploys in a customer VPC, on-prem, or as a Snowflake Native App, with SOC 2 Type II and outputs to Snowflake or Databricks.
Pricing: Trial key and demo on rockfish.ai.