Deploy machine learning in minutes and monitor performance in a scalable and secure environment.
Pre-trained models are automatically version controlled, annotated and hosted when uploaded, providing you with complete oversight on every model productionize.
Leveraging Kubernetes/Docker container technology, hosted models are capable of running independently and in parallel, providing scalability and security.
With multiple publishing options, end users can interact with a single hosted model in multiple ways including APIs, spreadsheet functions or through the everyday tools they use.
Usage and model metrics data collected provide real-time model analytics for real-time machine learning performance monitoring.
Error detection capabilities help you notice and address issues early on. Snapshots are taken every instance a model is run and provide visibility on inputs and outputs.