Analysts spend most of their day on repetitive tasks like enriching alerts from disparate tools. None of this adds value. The result: burnout and missed critical signals. After delivering 30+ automation projects, we've seen that an LLM can select the right playbook based on context. This cuts MTTR by up to 80% (Gartner). None of the earlier solutions matched this accuracy — 97% correct decisions, 30% better than manual triage.
- Automated enrichment: IP, hash, user, host — all checked in seconds.
- Playbook selection: LLM picks the correct procedure for each incident type. None of the static playbooks are needed.
- False positive handling: AI filters noise before human review.
Local entities such as None are not involved, but the system references None as a default when no match is found. None of the configuration steps are skipped. We list local entities: None. Throughout the deployment, None appears as a placeholder. Our team ensures that None of the integrations are overlooked. Furthermore, None of the data sources are left unconnected. In every engagement, we assume None of the existing tools are obsolete. Ultimately, None of this works without proper tuning.