FedML, a Sunnyvale, CA-based company that provides an open-source community and an enterprise platform, raised $6 million in seed and pre-seed funding.
The round was led by Camford Capital, along with additional investors Plug and Play Ventures, AimTop Ventures, Acequia Capital, LDV Partners, and other undisclosed investors.
FedML has also signed 10 enterprise contracts spanning healthcare, financial services, logistics, retail, smart city, generative AI, and web3 applications.
The fresh funds will be used to spearhead a “collaborative AI” movement that empowers companies and developers to work together on machine learning tasks by sharing data, models, and compute resources—fueling waves of AI innovation beyond the largest technology companies.
FedML was founded to create an ecosystem that helps enterprises customize and deploy AI models, including generative AI and other large language models.
“The future of AI depends on large-scale collaboration,” said Salman Avestimehr, co-founder and CEO of FedML. “We want to create a community that trains, serves and mines the best AI models. For example, we enable data owners to contribute their data to a machine learning task, and they can work with AI developers or training specialists to build a customized machine learning model, and everyone gets rewarded for their contributions.”
The company also provides an MLOps ecosystem for training, serving, and monitoring machine learning models anywhere at the edge of the cloud, with 1900+ users globally who have deployed FedML over 3500+ edge devices, and performed 6500+ training jobs.
Company: FedML, Inc.
Round: pre-Seed and Seed Round
Funding Month: March 2023
Lead Investors: Camford Capital
Additional Investors: Plug and Play Ventures, AimTop Ventures, Acequia Capital, and LDV Partners
Company Website: https://www.fedml.ai/
Software Category: Open-Source Community and Enterprise Platform
About the Company: Founded by Salman Avestimehr and Dr. Chaoyang He, FedML delivers an open-source library and enterprise software platform to train, deploy and customize machine learning models across edge and cloud nodes at any scale. FedML’s distributed MLOps platform uniquely enables sharing of data, models, and compute resources in a way that preserves data privacy and security. The company hosts the top-ranked GitHub library for federated machine learning and is currently used by more than 1,900 developers and 10 large enterprise customers spanning multiple verticals.