  The advent of next-generation X-ray free electron lasers will be capable of
delivering X-rays at a repetition rate approaching 1 MHz continuously. This
will require the development of data systems to handle experiments at these
type of facilities, especially for high throughput applications, such as
femtosecond X-ray crystallography and X-ray photon fluctuation spectroscopy.
Here, we demonstrate a framework which captures single shot X-ray data at the
LCLS and implements a machine-learning algorithm to automatically extract the
contrast parameter from the collected data. We measure the time required to
return the results and assess the feasibility of using this framework at high
data volume. We use this experiment to determine the feasibility of solutions
for `live' data analysis at the MHz repetition rate.
