Train your machine learning models on the data that is stored locally, is private, and doesn’t require you to send all the data to central locations with Devfi’s Federated Learning-as-a-Service. Our cutting-edge Federated Learning algorithms enable the deployment of collaborative machine learning models across various devices to learn from such decentralized data and transform them into intelligence with the least effort and no risk.
Inherent data privacy
Data privacy is at the heart of what we do at Devfi. By blocking access to the raw data in distributed datasets, we keep your data private and secure.
Heterogeneous data access
Federating the algorithm training and preserving the privacy of the data will help you quickly unlock access to diverse and valuable data sets.
Real-time continuous learning
Streaming real-time data allows for continuous learning and speeds up the training process by allowing for the federation and parallelization of data. Quickly gain access to trained models and insightful information.
Distribute your data among multiple locations and train models on them concurrently. This will enable you to train faster with less computational power or storage space needed from each individual location.
How It Works
Enabling federated learning on every device by mitigating data privacy concerns and providing a transfer learning paradigm
Our products that enable diverse AI applications
Switch, an indigenous product offering from us, is a platform for distributed machine learning to unify any framework or programming language and accelerate parallel data training across smartphones, edge, and other devices.
Get in touch with us to see how we can help you reach your goals and grow your business at a new level.