Dealing with 40PB of logs means you can't afford to have humans in the loop for every new data source.

We’ve built a pipeline that treats log ingestion as a dynamic feature engineering problem. By using schema inference and automated feature extraction, we feed raw telemetry directly into Energy-Based Models (EBMs).

The interesting part isn't just the ingestion—it's the feedback loop. When the system sees a new risk, it creates and optimizes a SOAR playbook via simulation. This post covers the "Step 1 to Step 6" of moving from raw text to an optimized, autonomous response.