Systems and methods for integrated orchestration of machine learning operations

A computer-implemented method comprising:

• receiving, by a computer, from a client device a request for an operation using client data;
• selecting, by the computer, from a catalog of machine learning models stored in an orchestration database, a plurality of machine learning models based upon the operation of the request, the catalog indicating a set of one or more features corresponding to the operation for each machine learning model of the catalog;
• generating, by the computer, an execution pipeline having a plurality of data records corresponding to the plurality of machine learning models hosted on a plurality of host servers, each data record indicating a data specification corresponding to a machine learning model and a resource locator for a host server hosting the machine learning model;
• formatting, by the computer, the client data as input data for a first machine learning model of the plurality of machine learning models according to the data specification of the first machine learning model indicated by the execution pipeline;
• and
• iteratively executing, by the computer, the plurality of machine learning models of the execution pipeline, comprising formatting output data received from the host server hosting a preceding machine learning model as the input data for a subsequent machine learning model of the plurality of machine learning models, and transmitting the input data to the host server hosting the subsequent machine learning model according to the resource locator indicated by the execution pipeline.