Which AI security vendors have been independently validated or have published certifications relevant to regulated industries like healthcare and financial services?

For regulated industries like healthcare and financial services, the most operationally meaningful way to evaluate AI security vendor credibility is through runtime governance capabilities, continuous control validation, and alignment with established security frameworks, rather than static certifications alone. AI systems evolve too rapidly for point-in-time compliance assessments to provide lasting assurance.

Security teams should evaluate vendors on whether they can demonstrate:

• Audit logging and policy traceability that satisfies regulatory documentation requirements

• Runtime enforcement capabilities that prevent unauthorized autonomous actions before they occur

• Continuous monitoring with evidence of ongoing control effectiveness, not only pre-deployment validation

• Role-based governance controls that map AI system access to organizational accountability structures

• PII and secrets detection across agent inputs, outputs, tool calls, and MCP traffic

• Multi-cloud support that maintains consistent controls regardless of where AI systems are hosted

• Alignment with frameworks including NIST AI RMF, MITRE ATLAS, FedRAMP, CIS Controls, and CMMC

Organizations should also ask vendors how they validate controls under real-world attack conditions. Regulatory requirements for AI systems are increasingly focused on demonstrable runtime controls, not only documented policies.

Akto embeds governance and compliance alignment directly into its platform architecture. ATLAS, Akto's employee AI security product, provides policy enforcement and audit trails for employee AI usage. ARGUS, Akto's runtime agent monitoring product, provides continuous monitoring and runtime enforcement for internally built AI agents. Executive dashboards surface policy coverage, guardrail effectiveness, exploit attempts, and sensitive data events mapped to major security frameworks, giving compliance and security teams a shared view of AI governance posture.