  This article presents a development of web application for quench prediction
in \gls{te-mpe-ee} at CERN. The authors describe an ELectrical Quality
Assurance (ELQA) framework, a platform which was designed for rapid development
of web integrated data analysis applications for different analysis needed
during the hardware commissioning of the Large Hadron Collider (LHC). In second
part the article describes a research carried out with the data collected from
Quench Detection System by means of using an LSTM recurrent neural network. The
article discusses and presents a conceptual work of implementing quench
prediction application for \gls{te-mpe-ee} based on the ELQA and quench
prediction algorithm.
