At a Glance
On Thursday, Lenovo announced an enhanced version of its health management SaaS tool, launched in March this year. This new version, Lenovo Device Intelligence Plus, builds on the features of the previous version and makes use of AI-driven predictive analytics to provide proactive data insights
Lenovo has launched an enhanced version of its SaaS-based health management tool, Lenovo Device Intelligence, in India on Thursday, reports state. The Lenovo Device Intelligence Plus, as it is called, is an enhanced extension of Lenovo’s AI-driven predictive analytics and also brings to the table, increased functionalities and proactive data insights.
The previous version, Lenovo Device Intelligence, was launched in March this year for enterprises, with a 60-day trial period. The tool was capable of assisting in the diagnosis of PC issues and also in predicting other potential system failures before they occur.
According to reports, Lenovo Device Intelligence Plus is capable of collecting over 10,000 data points every 15 seconds from every device and monitor millions of these aggregated data points in real-time. The tool would then report on device health trends and deep root-cause analytics and provide insights to inform decisions across hardware and software investment for better business outcomes.
Rohit Midha, director of service sales at Lenovo India, in a statement to media, said that the upgrade would optimize support costs, increase end-user productivity and improve customers’ overall end-user experience. It would enhance the previously launched version’s features such as advanced predictive analytics, proactive insights, robust reports, and fleet health scoring,
After carefully surveying customers to understand their largest unsolved IT pains, Lenovo developed an advanced predictive analytics solution with a flexible, extensible architecture and enhanced securityRohit Midha, director of service sales at Lenovo India
Regarding security, Lenovo assured that the version is built on a multi-layered security stack with strict data privacy policies and follows industry best practices. Protection measures such as secure encrypted APIs, Web-app firewall providing IP/domain whitelisting, and others are used, reports indicate.