“With model interpretability in Azure Machine Learning, we have a high degree of confidence that our machine learning model is generating meaningful and fair results, and we have the ability to understand the particulars of any individual case."
"Before we deployed Azure Sentinel, we literally didn’t know what we didn’t know. New alerts are showing up now, and we’re turning on additional reporting that gives us visibility across multiple tools in a single pane."
"Field associates need straightforward answers to fundamental questions By building the EVA chatbot with Azure Bot Service, we can now deliver those answers quickly and easily."
"Supervisors use data stored in Azure to determine work-load, staffing and how much utilisation they are getting from the equipment in their cell."
"With Asset Management we don’t have to step out on to the floor. We get real-time updates that let us know which cells are having issues, or whether it is something to do with our programme."
"Microsoft’s openness really works for us. With the speed of business so much faster today, we don’t have time for anything less. Microsoft is completely transparent about sharing its vast expertise."
“We’re very proud of the number of therapeutics and vaccines that Phlexglobal has been able to support to bring to the market over the years.”
“Microsoft Azure was picked primarily for the speed to market. It ties very, very well into our infrastructure.”
“There’s a 25 to 30 percent time improvement for individuals who are indexing those documents. By having those AI suggestions, we’re also seeing high degrees of confidence and accuracy coming from the AI models.”
"Microsoft Consulting Services offered us a strategic way forward, a way to get all the technologies and our people working together."
“We found that the concept of addressing both our people and our processes as part of our engagement with Microsoft was a winning formula for us.”
"Our ultimate goal is to collect, store, analyze, and return data from all global bases. We’ll incorporate new technologies into GAUDI as they emerge. It’s an ongoing initiative."
"GAUDI covers four concepts: collecting, storing, using, and feeding back data. The aim of GAUDI was to provide these functions quickly, economically, and on time by anticipating the needs of our users."
"Azure enables you to run the same modules at the edge, fog, and cloud from the get-go, which was exactly what we wanted with this project."
"The extensive range of Azure PaaS services, like Azure Machine Learning, is another great advantage. Combining containers and various Ops delivers extremely efficient operation."
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