Assess, test, monitor, and collaborate on AI security — all from one embedded team backed by our proprietary platform. Build trust in your AI systems that you can prove to customers, auditors, and regulators.
One team for assessment, testing, monitoring, and collaboration—not five vendors with conflicting reports.
Testing results automatically feed trust assessments. No manual data entry or report reconciliation.
ISO 42001, NIST AI RMF, HIPAA, GDPR, and more. Map your security work to the frameworks that matter.
Cryptographically signed Trust Marks that customers and auditors can verify independently.
A complete suite of tools for enterprise AI trust and security
Evaluate your AI systems against industry standards
Prove Your AI Systems Are Trustworthy
AI trust assessments against the ZIVIS Framework and major compliance standards. Generate cryptographically signed Trust Marks.
AI-Guided Evidence Collection
AI-conducted interviews that automatically gather evidence and generate actionable roadmaps.
Find vulnerabilities before attackers do
Adversarial AI Security Testing
Red team your LLM applications against OWASP LLM Top 10 with automated adversarial agents.
Infrastructure Security Testing
Traditional penetration testing for the APIs, web apps, and infrastructure surrounding your AI.
Security for Autonomous AI
Purpose-built testing for AI agents with tool access, excessive agency detection, and boundary testing.
MCP Server Security
Security testing for Model Context Protocol servers and integrations.
Continuous visibility into AI security
Share trust with stakeholders
Expert guidance for AI security
Every product feeds into your overall trust posture
Red team findings automatically map to trust assessment controls
Evidence collected in interviews populates your evidence library
Monitoring data demonstrates ongoing security posture
Share verified trust profiles with customers and partners
See how the ZIVIS team can help you assess, test, and prove the trustworthiness of your AI systems.