AI SOC tools today seem fixated onspeed—how quickly they can investigate and how many issues they can call falsepositives. But at AiStrike, we’re taking a slightly different approach.

Yes, speed is important, but instead ofjust rushing to triage alerts quickly, we’re more interested in understandingwhy the alert triggered in the first place, whether there are other relatedalerts, and tying the issues back to the root cause.

Just this week, we found several alertsthat looked completely different on the surface but were actually flagging thesame underlying issue. Turns out, there were redundant tools—one native and onethird-party—monitoring the same resources. All that extra noise and cost fornothing. By shutting down one of the tools, our customer saved significantmoney without compromising security.

The lesson? It’s not about speed alone.It’s about actually helping customers understand their exposure and the rootcause so the issues can be fixed strategically, not just patched over.

This approach also helps customers tunetheir detection engineering, which AiStrike automates with human-in-the-loop,so their security posture keeps getting better over time.

I keep wondering: Is alert-based pricingactually working for customers, or is it working against them? Because if thepricing model rewards noise, how much incentive is there to actually reduce it?