“We think telemedicine is perfect for direct pay, and we would like to see it continue because that will turn the actual cost benefit of doing telemedicine into a price benefit.”
“With the help of Servian, we migrated to Google Cloud in eight weeks with minimum developer input and maximum performance output,” says Danny. “Google Cloud gives us more time to focus on building customer-facing product features rather than managing infrastructure tasks.”
"When our customers ask about reliability and security, our answer is that this is as good as it gets. We tell them that we run on Google Cloud Platform."
“We integrate digital networks for our customers globally. As we continue to drive deeper customer engagement and expand into new geographies, data-driven decision-making becomes critical. STL’s data lake, built in Google Cloud, empowers us to do that by securely managing and analyzing large volumes of diverse business data. It has …
“Our business is all about data networks. With the help of BigQuery, we can use data internally to make the right decisions or even to make timely surgical interventions, be it around the efficiency of our manufacturing processes or the predictive models for our quantitative and qualitative performance metrics.”
“Our architectural landscape and transformation design principles enabled us to avoid running separate data warehouses. Creating a data lake enabled us to extract deep insights from historical and real-time data from disparate sources in a unified, clean format. This is a great benefit and big time saver for us.”
"Our trigger for change came from the strategy. Continuing with a traditional hosted service wasn't sustainable in view of the growth we were expecting, so we knew we had to move into the cloud. We saw that as an opportunity to transform our architecture."
“We needed a better way to grow with our data.”
"We envisioned that all software will be written with the use of AI in the near future, whether it was in creating software, in reviewing it or deploying it, and probably all three. When we started this sounded like a dream but now, it is an everyday reality."
"We currently have more than 150 machine learning (ML) models and are adding more as the complexity of our product grows and we add more features for customers With Google Kubernetes Engine and Cloud Run, each ML model can operate independently, allowing greater flexibility for the team."
“We wanted to provide enterprise reliability and quality at prices smaller businesses can afford.”
"We were looking for security to go for a full platform deployment, minimizing risks. We chose Google Cloud due to network traffic requirements, one of the cloud’s strengths. As for mass data processing, Google Cloud’s team helped us with the project and supported everything tech-related."
"One of the outstanding achievements is the time it takes to properly install an app in production, which is just five minutes. We have also seen a service level agreement (SLA) for responding to complex requests below the 90 seconds mandated by regulators."
"Agricultural insights tend to exist in siloed databases. BigQuery allows us to connect various data sources where no connections previously existed. We were the first company to bring it all together, to give our customers the big picture of their crops."
"Knowing the best time to spray can mean using less pesticide or even a non-toxic alternative in a more targeted area. This is much better for growers and ultimately for consumers. This can lead to lower costs for growers and respond to growing consumer pressure to reduce the use of …
FeaturedCustomers has 1,910,477+ validated customer references
including reviews, case studies, success stories, customer stories,
testimonials and customer videos that will help you make better
software purchasing decisions.
