RiskGrid AI is an AI-native cybersecurity platform built to secure the software development lifecycle with better context from design to audit
RiskGrid AI is an AI-native cybersecurity platform built to secure the software development lifecycle with better context from design to audit. Modern security workflows are fragmented. Architecture reviews, threat models, code security findings, pentest results, privacy requirements, and compliance evidence often sit in different tools and systems. RiskGrid AI brings these together through one shared security context layer. Our Aegis Suite supports secure architecture review, threat modeling, application security, offensive validation, privacy-by-design, and GRC, helping security and engineering teams understand risk in context and carry that context across the SDLC. We use agentic workflows, security memory, evidence-backed analysis, and human-in-the-loop validation to help teams reduce noise, prioritize real risk, and move from findings to action faster. Our focus is simple: make security more connected, context-aware, and practical for the AI-accelerated software era.