Do you have the quality and volume of data necessary? How do you know you need ML over traditional analytics? What is your data strategy? Have your model prototypes shown causation or correlation?
Assess how close your business is to being able to build reliable ML products and identify concrete steps needed to be successful.
Do you have infrastructure capable of hyper-parameter optimization, model evaluation, automated training and retraining, version tracking and governance, or model and drift monitoring? Is your data centralized, clean, and ready for ML?
A technology backbone that provides you with all the capabilities required to successfully scale and operate an ML environment. We can develop your whole environment or lead specific components.