Organizations that use Sarus outperform their peers at execution speed for machine learning and analytics while being more secure. Learn how.
Sarus makes machine learning deployment faster and safer by alleviating data access constraints.
Deploying a ML model on foreign branch requires accessing confidential information from the foreign customers to validate and possibly tune the algorithms. Granting access across regulatory borders adds months to the deployment process.
With Sarus installed on the branch data infrastructure, data teams instantly connect to the dataset without seeing it. They can explore the data thanks to synthetic data, refine feature engineering and tune models, without ever having accessed the data itself.
Models are deployed in hours instead of months across business units and countries. Suspicious activity (fraud, money laundering…) is prevented and customer experience is enhanced everywhere.
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