Open-source frameworks and languages have overtaken their proprietary black-box counterparts and nowadays, without exaggeration, can be considered data scientists’ top choice. Whether Spark, TensorFlow, Torch, Python or R, notable aspects often mentioned in this context besides the free open-source nature are the large community of active contributors and the resulting availability of packages on the public repositories and GitHub, as well as the conceptual design choice of facilitating and embracing interfaces with other languages, services and systems.
At Mirai, we have lots of experience in building and deploying customized Python and R based analytic applications, services and collaborative environments in constrained enterprise IT landscapes and hosted by large cloud providers such as MS Azure, AWS or GCP. You can see an overview of our projects in re-/insurance (and finance) in the images below.
In combination with the popular framework Shiny, visualization and reporting libraries such as plotly, leaflet and quarto, as well as our commitment to developing state-of-the-art reactive solutions, we have the know-how and the toolkit to build rich interactive end-to-end applications — allowing you to communicate key data and business insights effectively among relevant stakeholders in your organization.