FAQs
Yes, and in many cases, it should. Synthetic data pipelines today offer control, coverage, and label quality that real-world datasets can’t easily match. In edge-heavy environments or when rapid iteration is required, synthetic approaches often outperform traditional methods.
Real data may still assist in benchmarking or tuning, but it is no longer required to train production-quality models.
Real data may still assist in benchmarking or tuning, but it is no longer required to train production-quality models.
No. Older platforms required deep simulation expertise or dedicated 3D teams. That’s no longer necessary. Newer platforms abstract the technical work, allowing teams to generate and annotate data from natural-language prompts, without handling 3D assets or scene configuration manually.
Nearly all major architectures, including YOLOv8, RT-DETR, DINOv2, and custom backbones, can be trained using synthetic data. Many platforms allow exporting datasets or integrating directly with training pipelines.
No. Many synthetic data platforms handle the 3D modeling, animation, lighting, rendering, and annotation automatically. You can describe what you want and receive a labeled dataset, without ever opening a modeling tool.
No. All assets are created by our team specifically for your project. You do not need to provide 3D models, scene files or images.
You do. You paid for them, so you are free to use them however you like. We only ask that you do not share them with other organizations or use them in ways that violate human rights standards.
Delivery can take anywhere from a few hours to a couple of weeks, depending on whether a 3D model already exists. The process is transparent, and we provide updates at each step.
Yes. You can use it across any number of projects within your organization. Our only requests are that it not be shared outside your company and that it is used ethically.
We offer a two-week money-back guarantee if you are not satisfied with the final deliverable. We just ask that you give us a chance to resolve any issues first so we can fix them and improve.