the right data For
your vision model
Deep learning models need large amounts of training data, and it is difficult to ensure the right data is collected and annotated to improve performance.
SBX generates synthetic data to build and improve computer vision models. Synthetic data avoids the costly and slow collection + annotation requirements of using real data alone. Iterate faster and build vision models with stronger performance.
Synthetic Data
Training with synthetic data is the best way to build and improve computer vision models. SBX matches real-world sensors and scenes to generate endless simulated variations.
Hybrid Data
By combining a small amount of real training data with a large synthetic set, models reach peak performance. Rapidly iterate on datasets to solve real-world vision tasks.
Vision Models
Save the compute time needed for training with SBX vision models. Data is a critical step to building a vision model, but when time is of the essence, it’s useful to skip development.
better vision Models
with SBX Robotics
Synthetic data is an exciting new way to accelerate computer vision. Training with synthetic data produces robust deep learning models, using only a small fraction of real data. Using synthetic data is the right way to build and improve computer vision models
Companies who choose us
Case Study
Detecting forklifts with OTTO Motors
The team at OTTO Motors looked to SBX synthetic data to bootstrap and improve computer vision systems in their line of AMRs.
What Customers say
Try out our platform, it’s easy!
Share 25 images from your vision system, and we will generate an optimized training set of 25,000 annotated synthetic images.