10 Top Synthetic Data Companies and Startups to Watch in 2025

Synthetic data reshapes how industries access and use information by offering safe, scalable, and flexible alternatives to real-world data. These synthetic data companies generate high-quality, artificial datasets that protect privacy, reduce bias, and cut down the time and cost of data collection across sectors like healthcare, finance, mobility, and robotics.

This article spotlights 10 synthetic data companies focused entirely on synthetic data by developing platforms for realistic image generation, 3D simulation environments, structured data modeling, and privacy-preserving analytics. Their innovations mark a shift in how businesses approach data, enabling faster experimentation, better compliance, and more reliable outcomes.

Global Startup Heat Map highlights Emerging Synthetic Data Companies to Watch

Through the Big Data & Artificial Intelligence (AI)-powered StartUs Insights Discovery Platform, covering over 7M+ startups, 20K+ technology trends plus 150M+ patents, news articles & market reports, we identified 190+ synthetic data solutions.

The Global Startup Heat Map below highlights the emerging synthetic data startups you should watch in 2025 as well as the geo-distribution of 190 startups & scaleups we analyzed for this research.

According to our data, we observe high startup activity in the US and Western Europe, followed by India. The top 5 Startup Hubs for synthetic data are San Francisco, London, New York City, Berlin, and Palo Alto.

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Discover Emerging Synthetic Data Companies to Watch in 2025

We hand-picked startups to showcase in this report by filtering for their technology, founding year, location, funding, and other metrics. These emerging synthetic data startups work on solutions ranging from machine vision-based synthetic data and an AI-powered synthetic data platform to synthetic geospatial data and synthetic medical data generation.

1. Simulacra Synthetic Data Studio – AI-powered Synthetic Data Platform
2. Sightwise – Machine Vision-based Synthetic Data
3. Lemon AI – Synthetic Data Curation
4. brewdata – Synthetic Data Generation Platform
5. Synthera AI – Synthetic Financial Market Data
6. Sigmawave AI – Visual Synthetic Data
7. Synthetrial – Virtual Patient Data
8. AgileView – Synthetic Geospatial Data
9. LifeSyn AI – Synthetic Medical Data Generation
10. Skanalytix – Synthetic Financial Time Series Generator

1. Simulacra Synthetic Data Studio

• Founding Year: 2023
• Location: New York, NY, US
• Use For: AI-powered Synthetic Data Platform

US-based startup Simulacra Synthetic Data Studio develops an AI-powered platform for real-time synthetic data generation and causal scenario modeling. It integrates existing datasets with advanced causal AI to model cause-and-effect relationships. This enables researchers to derive accurate inferences and actionable insights.

The platform employs conditional generation to expand and rebalance datasets to simulate dynamic “what-if” scenarios and predict outcomes with precision. Simulacra Synthetic Data Studio’s platform reduces research costs, accelerates decision-making, and enhances the reliability of consumer and market analysis.

2. Sightwise

• Founding Year: 2024
• Location: Hannover, Germany
• Use For: Machine Vision Synthetic Data

Sightwise is a German startup that develops a modular software platform that utilizes synthetic data to enhance machine vision applications for industrial inspection tasks. The startup’s platform, Sighthub, integrates real-world data with AI-driven synthetic datasets to simulate diverse inspection scenarios. This enables precise defect detection and reliable visual quality assurance.

Sightwise’s solution supports integration with existing production environments and offers features like automated defect generation, photorealistic image rendering, and customizable inspection parameters. This accelerates AI model development and deployment, which reduces costs, improves inspection accuracy, and adapts to dynamic manufacturing needs.

3. Lemon AI

• Founding Year: 2024
• Location: London, UK
• Use For: Synthetic Data Curation

UK-based startup Lemon AI develops synthetic data models to enhance AI model training and fine-tuning. These encoder-only and decoder-only models curate datasets that address data scarcity and quality shortcomings. This ensures optimal representation and integrity.

The models offer automated rewriting and targeted augmentation. They enable users to build custom large language models (LLMs), manage data pipelines, and improve dataset structure. This reduces manual effort and accelerates AI advancements.

4. brewdata

• Founding Year: 2023
• Location: San Francisco, CA, US
• Use For: Synthetic Data Generation Platform

US-based startup brewdata develops a synthetic data generation platform that simplifies data creation through a user-friendly point-and-click interface. It employs advanced generative AI techniques, including generative adversarial networks (GANs), to produce high-quality synthetic data that mirrors the statistical properties of real datasets. The platform supports applications such as software testing, data sharing, and bias adjustment while ensuring compliance with privacy standards.

Further, brewdata automates processes like sensitive data masking and frequency distribution adjustments, which enhances efficiency and reduces manual effort. It democratizes data generation for users without technical expertise to create reliable synthetic datasets for secure data-driven solutions.

5. Synthera AI

• Founding Year: 2024
• Location: London, UK
• Use For: Synthetic Financial Market Data

UK-based startup Synthera AI develops a synthetic financial market data platform that generates realistic yield curves, stock prices, and foreign exchange (FX) rates using advanced generative AI techniques. It models dynamic, non-linear correlations and long-term dependencies to create diverse market scenarios. This enables professional investors to test portfolios and refine strategies with precision.

Synthera AI’s platform enhances simulations and captures a range of market conditions to minimize the risk in forecasts. This assists investors in uncovering new opportunities, mitigating risks, and making informed decisions that drive financial success.

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6. Sigmawave AI

• Founding Year: 2023
• Location: Singapore
• Use For: Visual Synthetic Data

Sigmawave AI is a Singaporean startup that develops platforms for generating visual synthetic data for the scaling of 3D worlds and diverse datasets. Its Terra platform employs advanced generative models and simulation techniques to create realistic images and videos that replicate real-world scenarios. These inputs enhance AI model training and testing.

Sigmawave’s other platform, Eclipse, supports applications in video intelligence for security and public safety. It offers features like automated labeling, customizable scene generation, and high-fidelity data outputs. The platform’s rule-based engine allows for camera-based event triggers, such as motion, intrusion area, and line crossing, tailored to specific detection capabilities.

7. Synthetrial

• Founding Year: 2024
• Location: Madrid, Spain
• Use For: Virtual Patient Data

Spanish startup Synthetrial develops a generative AI platform that provides virtual patient data derived from small samples of real patients. It uses advanced modeling techniques to predict future patient characteristics, forecast clinical trial outcomes, and enhance the statistical significance of trial results. The platform supports trials for cosmetics and cancer.

Additionally, Synthetrial offers features like dynamic scenario forecasting and reliable validation across trial types. This optimizes clinical trial processes, reduces costs, and improves research timelines to minimize patient risks and ensure reliable conclusions.

8. AgileView

• Founding Year: 2023
• Location: New York, NY, US
• Use For: Synthetic Geospatial Data

US-based startup AgileView develops a geospatial synthetic data platform that enhances object detection in machine learning applications. It uses a simulation engine to create 3D worlds as the foundation for synthetic satellite and aerial imagery. The platform incorporates multiple randomization factors, filters, and variation parameters to generate diverse and realistic datasets.

AgileView enables users to create and collect tailored training data by replacing real data while maintaining high accuracy and reliability in remote sensing model training. This addresses challenges like limited availability of images and poor data quality to optimize machine learning performance and advance geospatial intelligence solutions.

9. LifeSyn AI

• Founding Year: 2024
• Location: West Virginia, US
• Use For: Synthetic Medical Data Generation

LifeSyn AI is a startup based in the US that develops AI-powered synthetic medical data generation solutions to enhance healthcare analytics, medical imaging, and related applications. The startup employs proprietary generative models to create high-resolution synthetic medical images across modalities like magnetic resonance imaging (MRI), positron emission tomography (PET), computed tomography (CT), and X-ray. The platform also generates realistic synthetic patient records and clinical trial data.

LifeSyn AI ensures compliance with healthcare data regulations to maintain statistical accuracy while preserving patient privacy. The solutions thus allow healthcare professionals to advance diagnosis, treatment, and research with secure synthetic data solutions.

10. Skanalytix

• Founding Year: 2023
• Location: Hawthorn, Australia
• Use For: Synthetic Financial Time Series Generator

Australian startup Skanalytix develops a synthetic financial time series generator that creates realistic synthetic series mimicking the statistical properties of real financial data. It utilizes the graph-based computational approach of the unified numerical-categorical representation and inference (UNCRi) framework to model mixed-type datasets. It also captures stylized features like mean reversion, volatility clustering, and fat tails.

Further, Skanalytix supports data-oriented tasks, including prediction, clustering, and data imputation, while simulating market conditions and augmenting scarce datasets. Thus, this high-fidelity synthetic data enhances financial modeling, optimizes risk management, and enables data-driven decisions.

Discover All Emerging Synthetic Data Startups

The synthetic data startups showcased in this report are only a small sample of all startups we identified through our data-driven startup scouting approach. Download our free Industry Innovation Reports for a broad overview of the industry, or get in touch for quick & exhaustive research on the latest technologies & emerging solutions that will impact your company in 2025!