Keperlog

Cognitive Monitoring of Critical Infrastructures

IT and datacenter infrastructures generate a large volume of technical logs and events.

Under normal conditions, these flows are already complex to operate and analyze. In crisis situations, noise takes over and obscures what truly matters.
Traditional monitoring tools collect data and trigger alerts, but struggle to prioritize, provide context, and explain what is actually happening.

This approach is part of a cognitive infrastructure monitoring approach, designed to help teams understand and operate complex environments.

Cognitive Observability Model

From noise to operational understanding: This model illustrates how Keperlog transforms raw events into actionable information by taking context, time, and criticality into account.
It relies on Mistral models selected for their sovereign deployment capabilities and their suitability for constrained environments.

Vendor-specific understanding adapted to real-world context

Keperlog relies on a deep understanding of vendor messages, directly embedded into the analysis to provide the LLM with the knowledge required for proper interpretation.
Operators can then adapt explanations and recommended actions to their operational context without altering the original vendor information.
Result: fewer false positives and more relevant decisions.

Managing infrastructure noise

Network devices, servers, hypervisors, and facilities systems generate thousands of redundant events that are often difficult to exploit as-is.

Keperlog aggregates, deduplicates, and weights these flows to reduce noise and surface truly relevant signals.
The goal is not to hide information, but to make what truly matters in operations visible.

Understanding events in their context

An isolated event often has little meaning. It is its repetition, its correlation with other signals, and its technical context that reveal a real issue.

Keperlog analyzes timing, environment, and technical dependencies to interpret what is actually happening, rather than just triggering alerts.

Keperlog does not replace operators. It supports them.

By providing clear and concise analysis, it helps teams prioritize, diagnose, and respond more quickly, particularly during complex incidents.

Humans remain at the center, with clearer visibility and reduced operational stress.

Datacenter and On-Premise Deployment


Keperlog is designed for datacenter-first deployment, with strict isolation and fully controlled data flows.
Analysis and AI inference are performed locally on Keperlog nodes, using dedicated GPUs, with no data exported to the cloud.
Fully on-premise and autonomous dedicated versions can be deployed for the most sensitive and critical environments, while maintaining effective monitoring without oversized infrastructure.

For more information about Keperlog and its use cases, contact us.