Managed Agentic Threat Hunting

Daylight Managed Agentic Threat Hunting is a managed threat hunting service that combines expert-defined hypotheses with AI agent swarms to continuously investigate threats across an organization's environment. The service addresses three core limitations of traditional threat hunting: infrequent scheduling, the expertise and time demands of hypothesis-based hunts, and competition with alert-handling priorities. The workflow follows a structured pipeline: - A Daylight security expert defines the hunting hypothesis and selects structured analyses from a maintained catalog - AI agents execute deterministic queries against up to 90 days of historical telemetry, with all analyses running in parallel - A coordinated swarm of specialized AI agents conducts iterative, multi-step investigation, dynamically refining data rather than following fixed scripts - A central orchestration system tracks all iterations, records decisions, enforces execution limits, and maintains structured context - Outcomes are either fully explained or escalated into a full investigation and converted into new detections Two hunt types are supported: - Hypothesis-Based Hunts: Expert-defined behavioral pattern investigations targeting unknown threats, with dynamic investigation paths and findings escalated or converted into detections - IOC-Based Hunts: Triggered by new vulnerabilities, threat intelligence, or customer inputs; uses standardized playbooks for cross-source correlation across endpoint, identity, and cloud data with binary outcomes Key differentiators from traditional hunting and automated tools include continuous hunting coverage, business context integration, methodology transparency, threat intelligence integration, and the conversion of hunt findings into new detections.