Automating labor-intensive tasks with AI: The LAMaLearner
Developed by ONTEC AI and Schoeller, the LAMaLearner is an innovative AI designed to automate labor-intensive tasks. Discover how this cutting-edge solution transforms log management and enhances IT security in our detailed case study.
About Schoeller Network Control
Schoeller Network Control is a network security specialist. In 2014, the company was integrated into the TEC Group network, but it has existed for over 40 years, having been founded as Schoeller Electronics in Vienna in 1979.
Schoeller Network Control offers professional solutions in the field of IT and telecommunications and is particularly specialized in the analysis, optimization, and security of IT resources.
The solution
LAMaLearner stands for Log Analysis Machine Learner.
This artificial intelligence automates labor-intensive tasks in log management and SIEM (Security Information and Event Management) projects.
As a result, the AI can significantly reduce the normalization effort in these projects, structure complex log data, and enhance the security of IT environments.
The LAMaLearner learns autonomously and is thus robust against potential format changes in log files. Additionally, it can be seamlessly integrated into various log management systems, making it applicable in other companies as well.
In the following video, Tobias from the ONTEC AI team explains the technical background and benefits of the solution:
This video is in German. For other languages, please switch on captions.
The LAMaLearner was nominated for the eAward by Report Media due to its level of innovation. The eAward is an economic prize that recognizes digitalization projects in the DACH region and has been awarded since 2005.
Summary and key takeaways
The greatest strength of artificial intelligence is its ability to relieve humans of tedious tasks. This case study has proven exactly that.
By the way: The successor to LAMaLearner is LARA, a self-learning AI in the field of security management.