AI SOC Token Waste Use Case
Fix the Problem, Don't Just Triage It
Third-party AI SOC tools burn tokens triaging the same alerts over and over. Noisy detection? The AI writes the same "likely false positive" summary every time it fires — 10 times, 100 times, 1,000 times. Same problem. Same tokens. Same conclusion. Nothing changes.
That's not intelligence — it's expensive repetition.
How spotr.io does it?
spotr.io's AI SOC Analyst feeds back into the detection engine. When the AI identifies a pattern — recurring false positives, a threshold that's too sensitive, a model that needs tuning — it doesn't just document the problem. It fixes it at the source.
• Noisy detection? Adjust the model, not the triage queue
• Recurring false positive pattern? Tune it once, not triage it forever
• Tokens spent investigating? They produce a permanent fix, not a disposable summary
The Conversation
"Does your AI SOC just stop working when you hit your token limit?"
"Other AI SOCs spend tokens describing the same problem over and over. Ours spends tokens once — to fix it."