From Logs to Context:
Build Real-Time Security Context & Control to Detect Threats Before SIEM

Security detection is at another inflection point. In the AI era, attacks operate at machine scale and machine speed—automated, parallel, and continuously evolving. Detection fails not because of logic, but because context is generated and arrives too late for attacks at this unprecedented scale and speed.

At the same time, security telemetry has grown 10–100×—from GBs to TBs+ per day—driving SIEM costs into the millions while still failing to deliver real-time detection.

The past decade focused on optimizing what happens after ingestion: storage, indexing, and then querying, but this model is now breaking under both data scale and attack speed. The bottleneck has moved upstream, into the security data pipeline itself.

Take a simple example: a password spray or brute-force attack in progress. To detect it effectively, you need to know:

• How many failures happened within a time window?

• Is this source IP abnormal compared to its baseline?

• Is this targeting a critical asset?

• Does this lead to a successful login next?

 

But none of these answers exist in a single log line. Traditional pipelines generate signals and context after ingestion. By then, it’s already degraded, delayed, or lost.

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In our March webinar, we’ll break down how a real-time security context and control layer actually works, and why it’s the missing piece in modern detection. You’ll see how to: