OctoML, a Seattle, WA-based startup offering secure deployments of machine learning and deep learning models as a managed service, raised $3.9m in seed financing.
The round was led by Madrona Venture Group with participation from Amplify Partners.
The company intends to use the funds to expand its business reach among companies across the globe.
Led by Luis Ceze, CEO, Tianqi Chen, CTO, and Jason Knight, Chief Product Officer, OctoML is leveraging Apache TVM, an open source project originated by the founding team, to enable companies of every size to harness deep learning without tuning and securing models to each hardware configuration that a customer might need.
Apache TVM is an automated deep learning model optimization and compilation stack that powers efficient model deployment in major technology companies like Amazon, Facebook, Microsoft, Xilinx, and Qualcomm. It is backed by a community of more 270 contributors worldwide, including people from major tech companies and academic institutions.
The mission of the project is to enable data engineers to optimize and deploy models across a broad set of hardware in a portable manner.
A spinout of the University of Washington Allen School for Computer Science and Engineering, the company will offer a managed service for companies looking to securely deploy in multi-cloud and edge environments and ensure that the models stay up and running at peak efficiency.