Safe Federated Learning on Distributed Datasets
Devron is bringing cutting edge federated learning technology to enterprises through our decentralized cloud data platform, Synergy. It provides unprecedented access to your proprietary insights to ensure data privacy. Synergy helps data science teams build algorithms on federated data lakes using multi-party encryption, without the need to centralize data.
What is Federated Machine Learning?
Training algorithms on decentralized data.
Centralize insights not data.
Preserve privacy while increasing model generalizability.
1. Access All of Your Data
Synergy allows your data to reside in a decentralized architecture to maximize data privacy, while still giving you the ability to generate valuable insights.
3. Fits Your Data Stack
Our Synergy Platform
Synergy is the first cloud platform to offer a user experience focused on decentralized (federated) machine learning in order to simulate your enterprise data silos and test various federated learning machine algorithms. This allows for data science teams to test privacy preserving techniques quickly to avoid privacy leakage in production applications.
Synergy seamlessly integrates inside your Cloud Data Lakes, Warehouses and Data Processors to enable decentralized machine learning. Our Python SDK provides developer ergonimcs to integrate with Snowflake, AWS, Databricks/MLFlow, Spark, Jupyter and machine learning frameworks such as Tensorflow, PyTorch and Scikit-Learn.
2. Federated Learning Operations