Enables greater speed, accuracy, and efficiency in AI by creating deep learning models that bridge the gap between AI applications and the diverse range of devices found on the edge
Elevate AI at the Edge
OmniML optimizes AI/ML models that can be deployed to edge devices with improved performance and accuracy
OmniML provides automated hardware-aware neural architecture search that trains the model once and then can be deployed on any hardware
Update Device to AI-Powered
OmniML boosts ML performance and shrink ML size to offer powerful AI/ML capabilities on previous legacy hardware devices
Rapid ML to Deployment
OmniML MLOps automatically designs the best model given hardware and latency targets to make each step simple and easy
OmniML Empowers Customers
OmniML is working with customers in sectors such as smart camera and autonomous driving to create AI-enabled advanced computer vision for improved security and real-time situational awareness. Its model compression software, which is being tested in self-driving vehicles, can also have an impact across a variety of other industries. For instance, it can improve the retail customer experience and support safety and quality control detection for precision manufacturing.
OmniML in Action
OmniML solves a fundamental mismatch between AI applications and edge hardware and makes AI more accessible for everyone. OmniML’s technology enables and empowers smaller, scalable machine learning (ML) models with superior performance. It accelerates the deployment of AI on the edge – particularly computer vision – by bridging the gap between AI applications and the high demand they place on hardware. Developers will no longer have to optimize ML models manually for specific chips and devices; this will result in faster deployment of high-performance, hardware-aware AI that can run anywhere.
No need to trade accuracy with latency. Achieve your goal on accuracy, speed, and efficiency with our hardware-aware AI model.
Speed up time to market:
Reach production faster with our scalable and automated tools. With greatly reduced iterations, your engineering team can focus on their core competencies and leave the ML realization on hardware to us.
Scale up with existing hardware. No need for infrastructure changes and extra costs. Save from the expensive models, chips and cloud computing resources.
Reach out to us if you are interested in learning more about OmniML