Clouderizer Showcase: Deploy and showcase your Machine Learning models in minutes

Getting Data Science and ML projects into production is hard, harder than other software projects. Data Science teams need significant commitment and bandwidth from other teams (IT, Dev, Ops) to see their models working end to end with live production data. This causes delays before their model sees the light of the day, if at all. Diminishing interest and commitment from leadership teams is also identified as a reason for Data Science projects getting shunted. Clouderizer Showcase makes Data Science teams independent and in control. They can drag-n-drop and deploy their models in minutes. Showcase auto generates a modern web application, which not just allows internal teams and beta users to try the model but also offers leadership team visibility into tangible potential of the project. Model versioning, ground truth feedback, traffic analytics, scalable and secure deployment are few other features that Showcase offers. Showcase currently supports H2O MOJO and PMML model formats. Support for ONNX and python pickle files is on the way.