Rapid deployment machine learning system

A system comprising:

• multiple processors configured to operate an application programming interface;
• said application programming interface that:
• receives, at an edge classifier, a first request comprising a first image and a first natural language request relating to said first image from a customer computer;
• processes, at the edge classifier, said first natural language request and said first image through an automated machine learning engine to generate a first response comprising a confidence factor for the first response;
• when the confidence factor is above a first predetermined threshold, responds, by the edge classifier, to said customer computer with said first response;
• when said confidence factor is below said first predetermined threshold, transmits, by the edge classifier, said first natural language request and said first image to a first device,
• performs, at the first device, a human in the loop method comprising:
• causing, by the first device, said first image and said first natural language request to be displayed on the first device;
• and
• receiving, by the first device, a human response through said first device, said human response being a response to said first natural language request with respect to said first image;
• and
• transmitting, by the first device, said human response through said application programming interface to said customer computer;
• when said confidence factor is below a second predetermined threshold, transmits, by the edge classifier, said first natural language request and said first image to a cloud-based classifier;
• processes, by the cloud-based classifier, said first natural language request and said first image through a second automated machine learning engine to generate a second response comprising a second confidence factor for said second response;
• when said second confidence factor is above said first predetermined threshold, responds, by the cloud-based classifier, to said customer computer with said second response;
• and
• when said second confidence factor is below said first predetermined threshold, transmits, by the cloud-based classifier, said first natural language request and said first image to the first device, wherein the first device receives said first natural language request and said first image from the cloud-based classifier and performs said human in the loop method.