Security organizations need standardized threat intelligence workflows for consistent outputs. Manual research can be slow, inconsistent and difficult to scale. Threat indicators may be incomplete, contextual enrichment can vary in quality and turning analysis into actionable guidance for protection, response and recovery can take weeks. This creates duplicated effort and hinders intelligence sharing. Solution Check Point Research – the threat intelligence and research division within Check Point – developed Universe, an AI-powered research cycle that converts expert investigative knowledge into repeatable automation. Universe uses AIdriven multi-agent workflows and curated prompts that reflect Check Point Research’s analytical standards. It reverse engineers samples at scale, extracts and validates indicators of compromise (IOCs), enriches them with internal and public data and supports telemetry hunting14 by generating and executing hunting queries to confirm prevalence and expand the intelligence picture. It generates standardized outputs, including IOC context, relationships and confidence levels alongside detection rules, threat patterns, concise analyst reports and remediation recommendations. Governance is strengthened through consistent structure, a clear evidence trail and a closed-loop system that feeds validated outcomes back into future investigations