WaveOne builds an AI-native video compression system that integrates scene and object detection into encoding and decoding to allocate bits intelligently. The approach runs on ML accelerators in modern phones and servers, enabling deployment on edge devices and cloud platforms like AWS and Azure. WaveOne claims its models can reduce file sizes by as much as half, with larger gains in complex scenes, and can degrade gracefully under constrained bandwidth. The platform is designed to be compatible with ML frameworks such as TensorFlow, ONNX, and CoreML so models can be deployed like other accelerated software. The company has demonstrated results in papers and presentations but remains in a pre-alpha stage without a full-scale product. It plans to use recent funding to finish R&D, build infrastructure and APIs, run tests, and line up initial customers before raising more capital.

Total raised

$7M

Funding rounds

1

Latest round

Seed

Latest activity

Dec 2020