RAD Security offers an AI‑driven detection and response platform that consolidates data from over 60 cloud, container, and supply‑chain sources into a unified security lake. Its FusionAI engine and autonomous AI Workers automatically correlate alerts, investigate incidents, and remediate threats across multi‑cloud and Kubernetes environments, while RADQL enables natural‑language queries and automated compliance reporting.
Funding
Funding not disclosed
Founders
Product
Problem
Security teams contend with dozens of siloed tools that generate massive alert volumes, duplicate data, and fragmented context, leading to alert fatigue, slow incident response, and missed cloud‑native threats. Without unified visibility across cloud, runtime, and supply‑chain layers, organizations struggle to prioritize real risk and automate remediation.
Solution
RAD Security delivers an AI‑driven detection and response platform that aggregates signals from over 60 integrations spanning AWS, Azure, GCP, Kubernetes, EDR, and vulnerability scanners into a single data fabric. Its FusionAI engine correlates and enriches each signal with real‑time runtime context, eliminating false positives and surfacing only actionable findings. Purpose‑built AI Workers (e.g., CloudBot, VulnBot, GRCBot, RADBot) autonomously investigate, triage, and remediate incidents, while the natural‑language RADQL engine lets analysts query the entire security lake in plain English. The platform provides explainable decisions, audit‑ready evidence, and automated compliance reporting, enabling security operations to move from noisy alert management to proactive threat mitigation.
Target Audience
Primary customers are enterprise security operations centers and managed‑security service providers that need unified, AI‑augmented visibility and automation across multi‑cloud and containerized environments.
Features
- FusionAI core that ingests, normalizes, and correlates data from 60+ cloud, container, and supply‑chain sources in real time.
- eBPF‑based kernel sensors delivering continuous behavioral baselines for every workload without agents or sidecars.
- AI Workers (CloudBot, VulnBot, GRCBot, RADBot) that perform autonomous investigation, prioritization, and remediation actions across cloud, runtime, and compliance domains.
- RADQL natural‑language query engine that translates plain‑English prompts into deterministic, repeatable queries across the security data lake.
- No‑code workflow orchestration with explainable AI decisions, full audit trails, and role‑based access control (RBAC) for SOC‑2, PCI‑DSS, NIST, and FedRAMP compliance.
- Unified evidence room and customizable dashboards delivering real‑time risk scores, trend analytics, and one‑click export for board‑level reporting.
- Multi‑cloud and Kubernetes‑native support, including CSPM, KSPM, and CWPP capabilities with automatic SBOM coverage and supply‑chain vulnerability tracking.