Hello, Federated Learning.
Our innovative data science solution, Synergy, leverages federated machine learning to access more of your data where it resides. By increasing the volume of data, you reduce the time to value and increase model generalizability while preserving the privacy of data sources and methods.
Access more data
Reduce ETL overhead
Mitigate cyber risk
Shorten time to value
How It Works
Flexibility to Define Federated Learning for your Enterprise
Synergy SDK allows data scientists access to insights from data wherever it resides. This decentralized data architecture maximizes data privacy without compromising the accuracy of your predictive models. This means that the costly, time consuming and risky centralization normally required for machine learning can be a thing of the past.
Revolutionary Technology, Real Benefits
Leaving data at the source and employing powerful metadata encryption keeps your data secure from hackers and your organization compliant with regulations like the GDPR and CCPA. Synergy therefore minimizes your exposure to cyber and regulatory risk alike.
Understand the Process
Our algorithms take you inside the black box, as all the models built within the platform offer explainability demonstrating how each federated data source impacted your model - giving your team confidence in your conclusions.
Integrate with mobile and enterprise applications using pre-existing access controls, data stores and software frameworks.
Secure Model Sharing
Secure model sharing via distributed model development, on device intelligence and privacy preservation.
Analytics teams can turn information into intelligence and present findings with tools like Tableau, Qlik, and PowerBI.