By using our DataOps platform you can bring together the most popular technologies to deliver and run data projects easily, quickly, and reliably. Extracting, preparing, processing and delivering data to the teams that need it can be done in a fraction of the usual time. And once it’s live, it won’t let you down.
You know you own valuable data, but it remains scattered and underexploited. While your business expertise is strong, you lack a fully-fledged data team that can leverage trusted data to support your business needs. Saagie can help you tackle this digital transformation by guiding you through your first POC. Our customers include public sector organizations that have successfully launched business intelligence use cases to make data-driven decisions before undertaking more advanced projects.
You finally built a data team and they started working on a couple of business use cases, but they’re struggling to get past the experimentation phase. They’re up against a well-known roadblock: getting POCs to work on a local machine is relatively easy, but scaling up production is hard. Saagie lets your data engineers build robust data pipelines in the technologies they already know, with little to no Ops input. We’ve helped our customers in the service, retail, banking or defense industries quickly get results and operationalize their initiatives in advanced reporting, Customer 360, process automation, fraud detection and more.
You have an established data department with a multidisciplinary team that has solid experience in building a custom stack for each of their use cases. But perhaps you can’t afford to allocate so much time and so many resources on setting up and maintaining a solution that may not even scale to additional projects, and you want your team to focus on delivering business value instead. Saagie gives you a single collaborative platform to centralize and monitor all your data projects. Our customers in the industry and insurance sectors leveraged our DataOps platform to get up and running right away and address multiple use cases simultaneously, including predictive maintenance, supply chain optimization, risk management and churn prediction.