Typical use cases addressed

Signal-based data analysis and non-linear events correlation

In this table are represented typical use cases addressed, where LOGFORCE has demonstrated its efficiency in performing precise non-linear events correlations, revealing hidden pathways, in real time and at scale. We achieve this converting data into structured signals, enabling real-time processing through a set of patented algorithms, capable of performing non-linear event correlation at any scale and simultaneously. This approach ensures an unprecedented level of system performance by processing complex interactions with heterogeneous sources simultaneously, even when data are unstructured and/or non-normalised.

So doing, LOGFORCE consolidates experience sequences into actionable signals, effectively replacing traditional AI labelling systems. On this foundation, we’ve created a next-generation explainable AI stack, where traditional training paradigms are replaced by continuously injected experiential knowledge. These advanced inputs integrate seamlessly into models, automating the use of authentic and synthetic experience through an infinitely scalable framework.