This topic examines AI-driven vulnerability detection and remediation platforms that combine automated security operations, governance controls, and domain-specific AI to identify, prioritize, and fix risks. As organizations deploy more AI agents and GenAI-enabled services, security tooling has shifted from alert generation to automated triage, investigation, and response—while regulators and insurers demand verifiable controls and audit trails. That intersection makes comparison of detection vs remediation, explainability, and governance essential in 2026. Key categories and tools illustrated by the provided platforms include: agentic SOC automation (Radiant Security), enterprise AI governance and policy orchestration for regulated firms (Monitaur), and GenAI-enabled operational platforms that expand attack surface and operational controls (Observe.AI). Radiant represents platforms that ingest signals across stacks, automate triage and response workflows, and retain audit records. Monitaur reflects governance solutions centralizing policy, monitoring, validation, and vendor risk management—important for insurance and other regulated sectors. Observe.AI highlights how conversation-intelligence and voice/chat AI in contact centers create both productivity gains and new detection/remediation needs (real-time assist, auto QA, and voice agent monitoring). When comparing platforms, consider detection fidelity, remediation automation (patch orchestration, playbook execution, rollback), integration with existing security stacks, explainability and human oversight, auditability for compliance, and vendor/governance features for regulated industries. Trade-offs include speed versus false positives, scope of automation, and domain specialization (e.g., contact centers, insurance). With rising regulatory scrutiny and broader AI adoption, organizations should evaluate tools not only for technical coverage but for governance, traceability, and vendor risk controls.