RYVER enables medical AI teams to generate
high-quality radiology images with annotations
reducing time and cost in data acquisition.
Use RYVER generative models to augment your proprietary data and oversample underrepresented subgroups.
RYVER models add diversity by being pre-trained on rich medical data from multiple partners.
Save 80-90% in cost per image by substituting data acquisition and annotation efforts as our models provide annotations on pixel level.
Generate additional data in minutes instead of months enabling your AI teams to focus on building and iterating quicker than ever.
RYVER generative models are pre-trained on high-quality medical imaging data sets. They can easily be fine-tuned with your
proprietary data without compromising data security or privacy.
RYVER python libraries enable you to easily integrate generative models into your data pipeline and generate synthetic data with
only a few lines of code.
RYVER provides a range of frameworks and tools to quickly assess the utility of synthetic data, including embeddings and the evaluation of downstream performance improvement of diagnostic models.
Synthetic data resources can be easily discovered through a graphical interface and used through a python library. The usage is automatically documented to eliminate
manual compliance work.
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80331 München
Germany