Take full control of your deep learning model development
using synthetic training data.
ANY COMPUTER VISION USE CASE
FULL STATE KNOWLEDGE
Generate and train on diverse and balanced synthetic datasets of virtually any size.
Rare and even impossible to acquire vision data is made possible by synthetic data.
Solve for edge cases as they emerge.
Pixel-perfect segmentation and custom labels, occluded keypoints, 6D pose, and much more.
"Synthetic data from Zumo Labs will help Thales develop cabin automation solutions that decrease congestion, facilitate aircraft disembarking, and manage passenger flow."
"Zumo Labs is building a future we can all trust by reimagining with airlines the way people travel."
"The dark room use case that we've been working on with Zumo Labs is something that there'd be no way for us to gain ground truth on."
Thales Group CEO
Deep learning development has long been throttled by traditionally sourced static datasets. Synthetic data is a dynamic approach to dataset creation, using CGI and 3D rendering engines.
Synthetic data targets some of the core needs in training data—versatility, volume, and quality—while reducing bias, improving representation, and completely eliminating privacy concerns.
It’s data that improves through rapid iteration cycles, increasing the efficiency of your model development.
Synthetic Data Solutions
I'm looking for custom synthetic training data solutions.
Does your computer vision model have specific training needs? Is collecting the perfect dataset to train your model difficult or time consuming?
Or do you just need pixel-perfect, pre-labeled data for more complex problems?
We'll help you take full control of your deep learning model development using synthetic data.