Synthesis AI — Synthetic data for computer vision
Synthesis AI is a synthetic data generation platform for training unbiased computer vision models.
Synthesis AI provides a simulation and synthetic data platform that enables companies to generate high-fidelity 3D data for training computer vision models. It is designed for machine learning engineers and product teams in the automotive, security, and consumer electronics sectors who need to eliminate data bias and ensure privacy compliance. The platform automates the creation of pixel-perfect labeled datasets, allowing businesses to simulate rare edge cases that are difficult or dangerous to capture in the real world. By using Synthesis AI, organizations can bypass the high costs and logistical hurdles of manual data collection and labeling. The software generates diverse human models and environments, which is essential for developing ID verification systems and augmented reality applications. You can find detailed breakdowns of such data-centric platforms on surfai.app to help scale your AI infrastructure. Synthesis AI ensures that all generated data is inherently privacy-compliant, as no real-world personal information is used in the synthesis process. For automotive manufacturers, the tool provides critical simulations for driver monitoring and pedestrian detection. It also supports virtual product design and spatial computing for XR developers requiring accurate 3D spatial labels. Business owners can choose from various synthetic data packages to accelerate their production timelines and improve model performance. Pricing is based on project requirements, and interested teams should contact sales for custom enterprise quotes or trial access.
- Pricing: enterprise
Specifications
| Pricing | enterprise |
|---|---|
| Integrations | TensorFlow, PyTorch, AWS S3, Google Cloud Storage, Unity, Unreal Engine |
| Best for | machine-learning-engineers, product-managers, automotive-manufacturers, security-firms |
| Website status checked | 2026-10-19T18:01:55.543+00:00 |
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|---|---|---|---|
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