Devron leverages federated machine learning and privacy technologies to unlock access to data where it resides so you don’t have to incur the costs, time, and risks of duplicating it in centralized data stores. By increasing the quantity of data, you reduce the time to value and increase model generalizability - all while preserving the privacy of data sources and methods.
“Devron’s technology has the potential to alter the data science and AI landscape!”
Devron's 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.
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. Devron therefore minimizes your exposure to cyber and regulatory risk alike.
Our algorithms take you inside the black box, as all the models built within the platform offer explainability, demonstrating how each federated data source impacts 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 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.