ODYSSEE, is an innovative platform with a rapid ROI, allowing to build specific skill tools involving industrial data analysis.

Available in modules, it allows to adapt easily to your needs.

" ODYSSEE was introduced to Advanced CAE Division at Toyota Motor Corporation on October, 2016."
Toyota Motor Corporation

"ODYSSEE Artificial Intelligence solutions offer new perspectives for the analysis and exploitation of Ariane 5 flight data"
B. Troclet, Senior expert in Structural analysus, Airbus Safran Launchers 

 

 Why ODYSSEE ?

Industrial data analysis (BIG DATA)

Numerical simulation or experimental data analysis

  • System complexity identification and control;
  • Predicting behavior in real-time ;
  • Time saving in optimization and/or automation of industrial processes; ...
  • Integrated solutions for on-board computing;
  • Decision support;
  • Improve correlations experiments / calculation; ...

 

The ODYSSEE plateform
Module offering a simple and effective analysis of industrial data.
Strengths :
  • Visual data analysis;
  • Mixed data analysis (quantitative & qualitative);
  • Data analysis by geographical area;
  • DSM analysis.
Module for generating data processing scripts without programing.
Strengths :
  • A Calculator appearance;
  • Efficient indicators available;
  • Efficient data mining algorithms;
  • Multiple media reading: files, matrices, vectors, executables, etc.
Post-processing and sensibility analysis tool.
Strengths :
  • Visual tool;
  • Reading database csv files;
  • Efficient interpolation algorithms.
Application Chaining Tool.
Strengths :
  • Visual tool;
  • Many pre-built applications available;
  • Compatibility with python;
  • Reading of multiple media: files, matrices, vectors, executables, etc;
  • Post-processing web interface.
 
Tool to extract and replace data in a file.
Strengths :
  • Used by interface or command line ;
  • Allow the coupling between an optimizer and a third party software.
 
Module for temporal function prediction of a system using the "reduced model" method.
Strengths :
  • Validated and efficient model reduction algorithms;
  • Simple to run ;
  • On-board.
Design of experiments (DOE) generation and optimization.
Strengths :
  • Efficient Design of experiments;
  • General interface to connect with third-party softwares;
  • Compatibility with Quasar;
  • Efficient optimization algorithms.