Synthetic Data Companies

Datagen

Tel Aviv, Israel

Datagen is an Israeli company specializing in the generation of photorealistic synthetic data for computer vision model development. Their core technology utilizes programmatic control over scene generation and domain randomization to produce large, diverse datasets with pixel-perfect annotations. This allows companies in industries like automotive, security, and retail to overcome data scarcity and bias challenges, accelerating AI model training and improving performance, particularly for edge cases.

Gretel.ai

San Diego, United States

Gretel.ai is a synthetic data platform specializing in the generation of privacy-preserving datasets for AI development. Their technology focuses on creating high-quality, domain-specific synthetic data, particularly for advanced applications like agentic AI and conversational AI workflows, leveraging integrations with tools like NVIDIA NeMo. Gretel.ai targets AI developers and businesses seeking to overcome data scarcity and privacy challenges when training and deploying complex AI models, addressing a rapidly growing market projected to reach 75% adoption by 2026 according to Gartner.

Tonic.ai

San Francisco, United States

Tonic.ai provides synthetic data generation solutions for software and AI development teams. Their platform creates realistic, fully relational datasets – including mock APIs – that mirror production environments while preserving data privacy and ensuring regulatory compliance through advanced redaction and synthesis techniques. Tonic.ai targets organizations needing comprehensive test data, particularly those working with sensitive information or lacking sufficient production data for robust development and QA processes.

Cognata

Rehovot, Israel

Cognata develops a physics-based, high-fidelity simulation platform for the autonomous vehicle industry. Their platform generates realistic and scalable synthetic data – including diverse scenarios and edge cases – to accelerate the testing and validation of autonomous driving systems. This allows automotive OEMs and Tier 1 suppliers to reduce development costs and time-to-market by minimizing reliance on costly and potentially dangerous on-road testing.

MOSTLY AI

Vienna, Austria

MOSTLY AI is an Austrian company specializing in synthetic data generation for machine learning applications. Their platform utilizes generative adversarial networks (GANs) to create statistically accurate, privacy-safe datasets mirroring sensitive information. MOSTLY AI targets enterprises and data science teams requiring access to realistic data for AI model training and testing while adhering to data privacy regulations like GDPR.

Hazy

London, United Kingdom

Hazy built a synthetic-data platform that generates artificial datasets mimicking real, sensitive data so firms in finance and healthcare can develop and test AI while preserving privacy. Founded in 2017 in London; its principal software assets were acquired by SAS in November 2024.

SKY ENGINE AI

Warsaw, Poland

SKY ENGINE AI is a Polish-founded company providing a synthetic-data cloud for vision AI, generating fully annotated, multimodal synthetic data and domain-adaptation tools to train computer-vision models at scale for automotive, robotics, medical and defense applications.

zypl.ai is a Tajikistan AI company whose credit-scoring software helps banks in emerging and frontier markets automate loan decisions under uncertainty. Its zGAN technology generates synthetic data to make risk models more robust, and banks using its platform have issued over $400 million in loans across 13 markets. Founded in 2021 in Dushanbe, it has raised funding led by Prosus Ventures.

Lakmoos

Brno, Czech Republic

Lakmoos is a Czech AI startup that uses proprietary neuro-symbolic AI to simulate real consumer behavior for market research. Its platform lets enterprises run surveys, interviews and focus-group simulations against AI-modeled target groups, returning answers and the underlying motivations in minutes. The company was founded by Kamila Zahradnickova and Jan Polisensky.