Rendered.ai startup raises $6m to expand developer framework for synthetic data

AI solutions require large datasets for training, which is often a limiting factor when building AI capabilities. Real-world datasets based on physical sensor-based collection can be expensive, have bias and gaps, or even simply be impossible to obtain. Simulated or synthetic datasets can power AI applications for industries such as satellite reconnaissance, robotics, medical imaging, and security applications where real world data is limited.

Nathan Kundtz, Founder and CEO, Rendered.ai: "Synthetic data is an answer to the most pressing problems in AI. Many users focus only on generating static datasets. By offering access to a PaaS for iterative collaboration and data generation, we can help customers and partners adopt synthetic data as an innovative, cost-effective business capability."

Rendered.ai provides the first-ever developer framework for synthetic data. The platform integrates scenario generation, 3D model libraries, asset management, compute management, annotation, metadata management, and analytics in a single offering for generating content to train machine learning systems, for data labeling and annotation, and to validate and improve AI accuracy.

Chad Anderson, Managing Partner, Space Capital: "The utility of synthetic data is already obvious to customers, however most existing solutions are highly bespoke and unscalable. By providing an open platform, Rendered's approach will enable the broad adoption of synthetic data into existing enterprise workflows. "We have seen the capability and potential of Rendered's platform demonstrated with customers and we believe that it will become the gold-standard for synthetic data generation. We are thrilled to join the efforts of Nathan and the team at Rendered and look forward to continuing to support their growth into geospatial intelligence markets, which are hungry for their services."

The Rendered.ai platform is a cloud-native experience including a no-code configuration tool, imagery generation using high-performance compute, and microservices and APIs to characterize, integrate, and access data with enterprise systems. Rendered.ai enables teams of data scientists and data engineers to work together to configure sophisticated pipelines for data generation to fit their business needs.

Rendered.ai's users include leading commercial and governmental organizations, academic partnerships, and CV analytics firms.

www.rendered.ai