Security analysts at the UK Ministry of Defence (MOD) — and everywhere — face an overwhelming challenge: They can receive thousands of alerts daily, and distinguishing genuine threats from false positives in a timely fashion has become nearly impossible without technological intervention. The human cost is significant — over 70% of SOC analysts (across sectors)¹ report burnout, even while the MOD saw a 400% increase² in data breaches over the past five years. Organisations often respond by adding more tools, personnel, and (unnecessary) costs rather than addressing fundamental inefficiencies.

This unified data model brings together endpoint, network, and cloud telemetry in one searchable data view. Analysts can quickly pivot from alerts to detailed investigation without switching contexts. By eliminating the need for separate tools and their associated licensing costs, total security tooling costs can be reduced by approximately 25% while actually improving capabilities and reducing complexity. Investigation guides and prebuilt playbooks standardise response procedures while ML-powered detection rules identify threats that might otherwise be missed. 

For remediation, security teams can execute actions across distributed endpoints simultaneously — isolating compromised machines, killing malicious processes, or deploying patches without leaving the platform. This end-to-end workflow automation transforms what was once a multi-hour, multi-tool process into a streamlined operation.