OmniML builds a neural-architecture-search based platform to create smaller, hardware-aware machine learning models that run AI inference on edge devices. The company focuses on producing models that are efficient from the start rather than merely compressing existing models, driving orders-of-magnitude improvements on edge hardware. OmniML’s technology has been integrated into Amazon’s AutoGluon and Meta’s PyTorch and has won multiple competitions, with reported ML tasks running 10× faster on different edge devices. It is working with customers in smart cameras, autonomous driving, retail, and precision manufacturing to deploy computer-vision and real-time situational-awareness applications. The company aims to accelerate edge AI deployment by removing manual chip-specific optimization and delivering faster, more accurate, cost-effective hardware-aware models. Financially, OmniML announced a $10 million seed funding round to support product development and customer deployments. OmniML was founded in 2021 and is headquartered in San Jose, California.

Total raised

$10M

Funding rounds

1

Latest round

Seed

Latest activity

Mar 2022