Who uses Rendered.ai?

Rendered.ai was designed with two users in mind, who often have separate but overlapping job functions: Synthetic Data Engineers and Computer Vision Engineers.

Data Scientists and Computer Vision Engineers: Data Scientists and Computer Vision Engineers approach their business problem with a specific algorithm and learning task in mind. These users focus on how AI can gain a high-level understanding from digital images or video of how the real world behaves. This practitioner is solving a particular AI/ML problem, understands the limitations of the particular algorithm, and designs synthetic data to stretch those limits.

Synthetic Data Engineer: The synthetic data engineer is a practitioner who applies the principles of synthetic data engineering to the design, development, maintenance, testing, and evaluation of synthetic data for consumption by AI/ML algorithms. Competence in this art is obtained through the creation of multiple datasets, with multiple variations, addressing multiple AI learning issues. The experience set tends to be horizontal across multiple engagements and this person has gained domain expertise in profound and nuanced changes on synthetic data and its likely effect on generalized algorithms.

The Platform provides the following capabilities, targeted to each of these users:

Benefits for Synthetic Data Engineers	Benefits for Data Scientists and Computer Vision Engineers
Secure, collaborative environment	Secure, collaborative environment
Configuration Management	No-code dataset generation that is easy to use and master
GPU acceleration, with Compute Management abstracted away	Dataset Library Management
Easy containerization	Analytics and comparison tools for datasets
User friendly web experience for testing configuration and job execution	Domain matching (Cycle GAN-based)
Analytic tools to compare two datasets and their AI/ML outcomes	Analytic tools to compare two datasets and their AI/ML outcomes
3D asset generation and management	Automatic, flexible annotation generation
Example Channel/Application SDK	Rapid “what if” dataset creation
Cloud-based processing including asynchronous job configuration and execution	Consistency across projects
Easily integrated endpoints	Unlimited* content generation

Typical Rendered.ai workflows

Rendered.ai has been used for some of the following commercial and research applications:

Generating synthetic CV imagery to train detection algorithms for rare and unusual objects in satellite and aerial imagery
Generating simulated Synthetic Aperture Radar (SAR) datasets to test and evaluate SAR object detection algorithms
Embedding synthetic data as an OEM capability underneath a 3rd party x-ray detection system to allow end customers to test domain-specific detection of rare and unusual objects
Simulating microscopy videos of human oocyte development over time to train AI to recognize different developmental stages

*Unlimited refers to the Rendered.ai subscription licensing which allows a set number of users to generate datasets in a managed, hosted compute environment that does not limit the number of jobs run, pixels generated, or images produced.