FedML offers an MLOps platform that lets companies and developers train, deploy, monitor and improve AI models on cloud or edge devices while enabling collaborators to share data, models and compute resources. The platform can run custom models and open-source models, and users can create collaborator groups that sync AI applications across devices and add servers or mobile devices to contribute compute. FedML recently launched FedLLM, a training pipeline for building domain-specific LLMs compatible with libraries such as Hugging Face and Microsoft DeepSpeed. The company also aims to build a community of CPU and GPU resources to host and serve models, proposing incentives such as tokens or other compensation for contributors. Financially, FedML raised an $11.5M seed round at a $56.5M valuation and reports a total of $13.5M in its war chest inclusive of the new funding. The company has a 17-person team, about 10 paying customers including a tier-one automotive supplier, more than 3,000 users globally, and reports over 8,500 training jobs across more than 10,000 devices.

Total raised

$12M

Funding rounds

1

Latest round

Seed

Latest activity

Jul 2023