4Data Limited
4Data supplies unlimited, photorealistic synthetic datasets generated by mathematical models for training AI systems. The data is fully annotated, diverse, and scalable, offering a cost‑effective alternative to manual collection or AI‑based generation. Customers subscribe to access the synthetic data platform, paying for usage or volume to accelerate model development and improve performance.
- Artificial Intelligence
- Developer Tools
- Software Only
Funding
Founders
Product
Problem
Training AI models requires large, diverse, and accurately annotated datasets, but the manual collection and annotation of real-world data is often time-consuming, expensive, error-prone, and difficult to scale. This bottleneck hinders the development and deployment of robust AI applications.
Solution
4Data provides a synthetic data generation platform that leverages mathematical techniques to create unlimited, diverse, and complex datasets with precise annotations. This technology eliminates the need for extensive real-world data collection, enabling faster and more efficient AI model development. The platform allows users to generate tailor-made data for novel AI applications, including corner cases to improve model robustness. 4Data's synthetic data can be used to train a wide variety of AI models, including object detectors, segmentation models, pose estimators, optical flow estimators, and stereo vision models. The generated data includes a variety of annotations such as 2D/3D bounding boxes, segmentation masks, depth maps, surface normals, and optical flow vectors.
Target Audience
4Data's primary customers are AI developers and researchers who need large, high-quality datasets for training computer vision models, as well as organizations seeking AI consultancy services for designing and deploying AI solutions.
Features
- Parametric object design using mathematical equations to control shape and texture.
- Random scene generation combining designed objects with other random elements to create diverse and challenging scenes.
- Automated annotation generation, providing accurate labels for training AI models.
- Custom training pipeline to maximize AI performance with synthetic data.
- Model conversion to common formats for deployment.
- Data generation for various computer vision tasks, including object detection, segmentation, and pose estimation.