- AI Security
Secure AI You Can Trust. From Build to Production.
Whether you’re building AI into your product or adopting it across your organization, we help you move fast without the risk.
How We Help
Comprehensive security across the AI lifecycle
Building AI Products
For teams shipping AI features or platforms
Al Red Teaming
Adversarial testing before you ship
Adversarial testing before you ship
This is a transformational leadership training. It is not therapy and not a religious service. Participants from all backgrounds are welcome.
73% of production AI deployments have prompt injection vulnerabilities
ā OWASP 2025
Threat Modeling
Adversarial testing before you ship
Adversarial testing before you ship
Systematic identification of AI-specific threats across model interfaces, tool integrations, data pipelines, and supply chain components. Covers agentic AI attack paths including memory poisoning and tool misuse.
44% increase in attacks exploiting public-facing applications, accelerated by AI-enabled vulnerability discovery
āĀ IBM X-Force 2026
Agent Security ArchitectureNew
Zero-trust design for autonomous Al systems
Zero-trust design for autonomous Al systems
Security architecture reviews for AI agent deployments, MCP integrations, and multi-agent systems. Covers least-privilege access models, non-human identity lifecycle management, and agent behavior monitoring.
Only 29% of organizations feel prepared to secure agentic AI deployments
ā Cisco 2026
Supply Chain SecurityNew
Model provenance & dependency integrity
Model provenance & dependency integrity
Security architecture reviews for AI agent deployments, MCP integrations, and multi-agent systems. Covers least-privilege access models, non-human identity lifecycle management, and agent behavior monitoring.
Only 29% of organizations feel prepared to secure agentic AI deployments
ā Cisco 2026
Adopting AI Safely
For teams rolling out AI across the org
Al Program Development
Governance, policy & use-case review
Governance, policy & use-case review
Build operational AI governance programsānot just principles. AI system inventories, risk classification frameworks, cross-functional governance committees, and controls integrated into your existing GRC structure.
Only 14.4% of enterprises get full security and IT approval before deploying AI agents
āĀ ISACA 2026
Shadow Al DiscoveryNew
Find and govern unauthorized Al usage
Find and govern unauthorized Al usage
Assess the scope of unsanctioned AI tools across your workforce. Produce a tiered classification system (approved/conditional/prohibited), acceptable use policies, and approved tool catalogs with monitoring capabilities.
Shadow AI adds $670K to average breach costs; 57% of healthcare workers use unauthorized AI
āĀ IBM 2025 / Healthcare Brew 2026
Vendor Assurance
Third-party Al risk & security validation
Third-party Al risk & security validation
AI-specific vendor due diligence, contract clause reviews for liability and data/model rights, supply chain component analysis, and ongoing vendor security posture monitoring integrated into your TPRM program.
Vendor risk is now inherent riskātechnology providers are part of the compliance system
āĀ Corporate Compliance Insights 2026
Compliance ReadinessNew
NIST Al RMF, ISO 42001 & EU Al Act
NIST Al RMF, ISO 42001 & EU Al Act
Gap assessments, AI risk classification, policy development, control implementation, and audit-ready evidence packages. Layer AI governance onto existing compliance programs (NIST CSF, HIPAA, FedRAMP) using published framework crosswalks.
ISO 42001 certification is moving from differentiator to procurement requirement
āĀ Gartner 2026
Gartner
Cisco
Cisco
OWASP
AI Security FAQs
What types of AI systems can you assess?
We assess the full spectrum of AI systems: large language models (LLMs), machine learning pipelines, computer vision systems, recommendation engines, and custom AI/ML implementations. Our expertise spans both first-party AI development and third-party AI integrations.
How is AI red teaming different from traditional penetration testing?
AI red teaming requires understanding both traditional application security and AI-specific attack vectors. We test for prompt injection, model manipulation, training data extraction, adversarial inputs, and AI-specific business logic flaws that traditional pentesters miss.
Do you help with AI compliance and governance?
Yes. We help organizations build practical AI governance frameworks that enable innovation while managing risk. This includes AI use case review processes, risk assessment methodologies, acceptable use policies, and alignment with emerging regulations like the EU AI Act.
What frameworks do you use for AI security assessment?
We leverage OWASP Top 10 for LLM Applications, MITRE ATLAS, NIST AI RMF, and our own methodology developed from real-world AI security engagements. We adapt our approach based on your AI maturity and specific risk profile.
Can you help us evaluate AI vendors before we integrate their solutions?
Absolutely. Our AI Vendor Assurance service evaluates third-party AI solutions for security, privacy, and compliance risks before you integrate them. We assess vendor claims against actual security controls and help you make informed decisions.
- Ready to Secure Your AI?
Get a tailored AI security assessment
No generic playbooks ā just a plan built for your stack and risk profile.