Secure AI
Govern AI use, expose shadow AI, and secure LLM, RAG, MCP, and agentic workflows before they become unmanaged business risk.
Best For
- AI governance gaps
- Copilot and GenAI rollout
- MCP and RAG security review
Solutions
Vectris Group organizes consulting engagements around the business pressure you need to resolve: AI risk, cybersecurity program maturity, incident readiness, or governance and compliance execution.
Govern AI use, expose shadow AI, and secure LLM, RAG, MCP, and agentic workflows before they become unmanaged business risk.
Best For
Strengthen identity, vulnerability management, cloud security, operating models, and executive reporting without waiting for a full-time leadership hire.
Best For
Prepare for material incidents, run tabletop exercises, coordinate containment, and produce response plans that legal, IT, security, and executives can use.
Best For
Build audit-ready control evidence, vendor-risk programs, and governance workflows that fit into existing oversight structures.
Best For
AI Search Answers
An AI security assessment reviews the governance, identity controls, data flows, prompts, retrieval pipelines, agents, third-party tools, and monitoring around AI systems. The output should identify practical risks and map them to prioritized controls, not just policy language.
AI governance should extend existing risk, security, privacy, vendor, data, legal, and compliance processes. Most organizations do not need to restart their governance model. They need clear ownership, AI-specific control points, evidence requirements, and escalation paths inside the operating model they already use.
Yes. Vectris Group can describe engagement patterns, control lessons, and anonymized outcomes while withholding client-identifying details where confidentiality obligations apply.