Rendered.ai: Data Engineering Tools for Proveable AI

Procedural world generation and digital twin scraping/imports

Procedural modeling and geometry generation tools are built in

In our experience, lack of diversity in the dataset is the root cause of most synthetic data failures. To address this issue, we incorporate procedural models over static ones whenever possible:

Landscapes, Vegetation, Buildings, Oceans, and Cities
PLUS a large library of internal and/or user uploaded models

Globally accessible and ready to scale

We provide an easy-to-use graphical interface for dataset generation AND a complete set of APIs for access wherever you need it.

Data can be downloaded locally or used with cloud-based pipelines (including directly to your AWS S3 bucket) keeping data residency near a global set of analytics tools.

Our architecture is cloud native; meaning almost instantly scalable compute environments are at your fingertips for both dataset generation as well as training and AI deployment.

Node-based data programming for automated creation of a synthetic ATR library

Dynamic SAR Oceans

Flexible and Powerful

Our shared simulation domains allow us to produce cross-domain, integrated, multi-sensor simulations to support robust data-fusion models from a single simulation enivronment.

All of our rendering engines are GPU-accelerated (including our full-wave Synthetic Aperture Radar engine!) meaning you'll have access to massive compute available via GPUs.

If we don’t have something you need in our tools library, we can build it for you or give you API hooks into the simulation environment.