Where Security Work Breaks Down
Signal to Insight
The first breakdown happens at signal interpretation. Tools report the symptom, not the shape of the issue. Signals duplicate or conflict. Misconfigurations show up as ten separate findings across tools.
Teams spend hours reconstructing what happened, validating what's real, and deciding what matters now.
Insight to Action
Even when teams reach clarity, the second breakdown begins. Next steps live in different systems. Fixes move through handoffs, tickets, and Slack threads. Ownership is hard to track. Reporting slows down. Audit prep starts from scratch.
What's missing is the connective tissue—how signal becomes insight, and how insight drives action. RAD is designed to do both.
How RAD Works
RAD transforms security operations through three connected stages: comprehensive signal intake, runtime verification, and automated action through AI workers.
Signal Intake
RAD connects to your entire security stack—SIEMs, CNAPPs, IAMs, static scanners—ingesting signals unaltered, timestamped, and source-tagged.
Whether it's a runtime detection from Sysdig, a misconfiguration from Wiz, or a policy alert from AWS, all metadata and context stay attached through every layer of analysis.
RAD Reality Check™
As signals enter, RAD traces them against live environment behavior using deep CADR telemetry, behavioral fingerprinting, and eBPF monitoring.
This runtime verification joins findings with shared causes and defines scope from behavior outward:
- Monitors cloud environments 24/7
- Investigates and triages in real time
- Learns your infrastructure to catch threats others miss
- Result: Runtime-verified insights with root cause, affected systems, supporting evidence, and environmental context.
RADBots Take Action
Purpose-built AI workers act on validated insights:
- CloudBot: Maps blast radius and fix paths for misconfigurations
- VulnBot: Prioritizes CVEs, links to workloads, files tickets
- GRCBot: Aligns findings with compliance frameworks, pulls evidence
- RADBots work from insight structure—handling task generation, routing, ticketing, and audit prep automatically. Everything stays connected: findings link to actions, actions trace to environment.
What RAD Delivers
Faster Triage
Signals are validated and grouped against live runtime context, so teams see what's real and what it connects to, without chasing duplicates or rerunning scans.
Actionable Risk
Findings include blast radius, asset impact, and runtime presence. RADBots line up the right fix with the right owner, ready to move.
Embedded Evidence
Compliance work a in parallel. Controls are mapped, artifacts are pulled, and evidence stays attached to the finding it came from.
Linked Outputs
Every message, report, and ticket stays connected to source telemetry and validation logic: no screenshots, no swivel-chair, no data loss.
Work That Moves
RAD doesn't just describe what happened. It moves the work forward automatically and in context.
RAD Integrates With Your Stack
RAD connects at both ends. We support 20+ integrations across detection, posture, identity, ticketing, and messaging—with new ones in progress.
Slack
Github
Jira
Akamai
Crowdstrike
Cursor
Supports Modern Security Strategies
RAD identifies exposure, validates findings, and kicks off automated workflows to reduce risk across cloud, runtime, and data layers.
From collection to response, RAD covers the full lifecycle—built on its own runtime, cloud, and application data, as well as any additional context from your existing stack.
Teams use RAD to answer compliance questions with real evidence. Control mappings and reports come straight from the platform’s detections and telemetry.
AI workloads come with new risks. RAD gives teams visibility into models, tracks where data flows, and enforces policy without slowing innovation.
Put RAD’s AI To Work
