.avif)
Threat Hunting That Runs Continuously
Daylight turns threat hunting from a manual, limited activity into a continuous system. We combine expert methodology with agentic AI execution to run hypothesis-based and IOC-based hunts across your environment.
See Daylight in Action
Discover how our hypothesis-based hunts and IOC sweeps work
Why Threat Hunting Falls Short
Hunts Run Periodically
Most threat hunting happens on a schedule: quarterly, semi-annually, or ad hoc, leaving large gaps where threats go undetected. During those gaps, attackers can operate without being actively searched for.
Hypothesis-Based Doesn't Scale
Hypothesis-based hunts require time, expertise, and deep cross-system investigation. As a result, they’re rarely run, and limited to high-priority cases, leaving most potential threats unexplored.
It Competes with Everything
Threat hunting requires focused time from experienced analysts—the same people handling alerts. Due to competing priorities, hunts are often deprioritized or never completed.
Two Hunts. Complete Coverage
IOC-based hunts validate known threats. Hypothesis-based hunts uncover unknown or undetected activity.
Hypothesis-Based
Hunts
Uncover unknown threats
Expert-defined hypotheses targeting behavioral patterns
Agentic AI executes multi-step iterative investigation
Parallel analysis across your full environment
Dynamic investigation paths—not predefined playbooks
Findings escalated or converted into new detections
IOC-Based
Hunts
Validate known threats
Triggered by new vulnerabilities, threat intel, or your inputs
Standardized playbooks for speed and consistency
Cross-source correlation across endpoint, identity, and cloud
Up to 90 days of historical telemetry searched
Binary outcome: confirmed presence or clean bill of health
Two Broken Approaches. One Complete Architecture
Traditional threat hunting services and automated tools both claim to find what detections miss—but the approaches are fundamentally limited. Here's how Daylight compares:
Expert Brain. Agentic Muscle
Human intelligence defines the mission. A coordinated AI swarm executes it—in minutes, not weeks.
Hypothesis Definition
A Daylight security expert defines the hypothesis and selects structured analyses from a maintained catalog.
Data Extraction
Deterministic queries against relevant telemetry across up to 90 days of historical data. All analyses run in parallel.
Iterative Investigation
A coordinated swarm of specialized AI agents investigate in parallel—each step refining data dynamically, not following scripts.
Controlled Orchestration
Central orchestration tracks all iterations, records decisions, enforces execution limits, and provides structured context.
Outcome Determination
Either all activity is explained, or unexplained behavior is escalated into full investigation and converted into detections.
This Isn't Another AI Copilot
Most AI SOC solutions assist analysts with copilots or automate predefined tasks. Daylight is different.
End-to-End Execution
We execute the full threat hunting process, covering hypotheses through outcome. This goes beyond just assisting analysts.
Hypothesis-Based Hunts
We start from hypotheses and investigate behavioral patterns, enabling discovery of unknown threats—not just known indicators.
Adaptive, Not Templated
Every investigation step is determined dynamically based on the data. No predetermined scripts or fixed query sequences.
Scales Beyond Human Limits
Multiple analyses run in parallel, iterative investigations complete in minutes. Continuous coverage across large environments.
Controlled & Auditable
Deterministic starting points, bounded execution, and fully recorded investigation process. Transparent, reproducible, and auditable.
.avif)
