AI-powered SOC platform that triages alerts across any security tool
Radiant Security built an alert-triage platform for enterprise SOC teams using a modern cloud-native stack (TypeScript, React, Python, Go, Kafka/Kinesis) paired with LLM integrations (OpenAI, Anthropic, Gemini) and RAG. The tech mix—spanning ingestion infrastructure (Kafka, Kinesis, GCS), data lake architecture, and AI triage—reflects a company scaling toward real-time alert processing at volume. Active hiring leans engineering-heavy (4 engineers + 2 staff-level) against a 51–200 person base, indicating infrastructure and platform reliability remain blocking growth.
Radiant Security operates an AI SOC platform that ingests and triages alerts from any security vendor or sensor, automating analyst triage and reducing response time from days to minutes. The platform targets enterprise security teams struggling with alert fatigue and tool fragmentation, providing native log management from existing cloud storage (AWS, GCP, Azure) to eliminate vendor lock-in. Founded in 2021 and based in Pleasanton, California, the company is in active scaling mode: nine open roles across engineering, product, design, sales, and security, with hiring extending into Brazil. Core product surfaces include case management, investigation workflows, remediation actions, and dynamic alert classification powered by LLMs.
Frontend: TypeScript, React, Next.js, Tailwind CSS. Backend: Python, Go, Node.js. Cloud: AWS, GCP, Azure. Streaming: Kafka, Kinesis. AI: OpenAI, Anthropic, Gemini with RAG. Infrastructure: Terraform, Pulumi.
Core projects: AI triage platform, ingestion infrastructure, data lake architecture, case management and alert triage product, investigation workflows and response actions, and customer onboarding/implementation.
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Radiant Security's technology stack, projects, and hiring signals are inferred from public hiring and company data — career pages, public listings, and company web presence — then clustered and de-duplicated. Figures are estimates that refresh over time. Read our full methodology →
This is not an official vendor or customer list. It is a technology-adoption signal inferred from public data, intended for B2B research.