AI-driven vulnerability detection brings large language models and agentic systems into code, configuration and infrastructure security workflows. This topic examines OpenAI’s Daybreak alongside cloud ML platforms, conversational assistants and enterprise governance tools that organizations use to find, prioritize and remediate vulnerabilities. As of 2026-05-19, the field has shifted from experimental scanning proofs-of-concept to production integrations: security teams are embedding LLMs into CI/CD, SAST/DAST toolchains, and incident response playbooks while demanding privacy, explainability and measurable accuracy. Key solutions include OpenAI Daybreak (an OpenAI offering focused on automated vulnerability discovery and triage), Google’s Vertex AI (a fully managed platform for building, fine-tuning and deploying ML/GenAI models) and Google Gemini (multimodal models accessible via Vertex and Google AI APIs). Anthropic’s Claude family provides conversational analysis and code-review assistants; IBM watsonx Assistant targets enterprise virtual agents and no-code automation for security workflows; Cohere supplies private, customizable models, embeddings and retrieval for proprietary threat datasets. Kore.ai and Adept represent agent and agentic platforms for orchestrating multistep remediation workflows and automating actions in software interfaces, while Monitaur focuses on vendor governance, policy, monitoring and validation for regulated industries. Practical considerations driving adoption include integration with existing security tooling, model provenance, false-positive management, adversarial robustness and regulatory compliance. Organizations evaluate vendors by their support for private deployments, fine-tuning on internal telemetry, observability and audit trails. The result is a layered market where general-purpose LLM providers, managed cloud ML services and specialized governance platforms converge to make AI-assisted vulnerability detection operationally useful but dependent on strong governance and validation practices.