Assistance, not unreviewed autonomy
Large language models can help security analysts organize information, explain technical findings and produce consistent reports. They can also produce incorrect or unsupported conclusions if the workflow is poorly designed.
Calyvex focuses on bounded use cases where model output remains connected to visible evidence and an analyst can review, challenge or reject the recommendation.
Potential use cases
- Convert structured alert evidence into a concise incident summary.
- Extract relevant entities, timelines and investigation questions.
- Draft analyst notes and management-ready reports.
- Recommend next investigation steps with stated uncertainty.
- Standardize repetitive triage and escalation documentation.
- Evaluate prompts and outputs against controlled test cases.
Safeguards
The design should minimize unnecessary exposure of sensitive data, prevent unsupported automated actions and maintain auditability. High-impact decisions should remain governed by appropriate approval processes.