  Process mining techniques including process discovery, conformance checking,
and process enhancement provide extensive knowledge about processes.
Discovering running processes and deviations as well as detecting performance
problems and bottlenecks are well-supported by process mining tools. However,
all the provided techniques represent the past/current state of the process.
The improvement in a process requires insights into the future states of the
process w.r.t. the possible actions/changes. In this paper, we present a new
tool that enables process owners to extract all the process aspects from their
historical event data automatically, change these aspects, and re-run the
process automatically using an interface. The combination of process mining and
simulation techniques provides new evidence-driven ways to explore "what-if"
questions. Therefore, assessing the effects of changes in process improvement
is also possible. Our Python-based web-application provides a complete
interactive platform to improve the flow of activities, i.e., process tree,
along with possible changes in all the derived activity, resource, and process
parameters. These parameters are derived directly from an event log without
user-background knowledge.
