From LLM vulnerability testing to AI governance compliance — we work alongside your security and AI teams to ensure your AI systems are safe, robust, and regulation-ready.
Not sure where your AI security gaps are? Book a free 2-hour AI Security Briefing. We'll assess your landscape and recommend a starting point.
Book Free Briefing →Looking for EU AI Act compliance? Fixed-price assessments, free pre-assessment, NIS2 cross-mapping — on our new compliance line.
AI Act Compliance & Assurance →Structured, evidence-based safety testing of LLM-based applications against 11 AI governance principles — mapped to AI Verify, EU AI Act, and NIST AI RMF. We test for hallucination, undesirable content, data disclosure, and adversarial prompt attacks using industry-standard benchmark datasets (MMLU, MLCommons AILuminate, CYBERSECEVAL 4, Microsoft BIPIA). Every engagement delivers a scored AI Safety Summary Report with an Independent Comfort Statement.
Identify, test, and remediate security vulnerabilities in your AI systems. From chatbots to autonomous agents — ensure they're safe before and after deployment.
Complete inventory of your AI systems, risk classification per OWASP Top 10 for LLM & Agentic Applications, threat model mapping, and EU AI Act gap analysis — delivered as a priority-ranked remediation roadmap.
Comprehensive AI security testing combining automated vulnerability scanning (Garak, DeepTeam, Moonshot) with manual expert red teaming across all OWASP LLM Top 10 categories.
Production-grade guardrails for input validation, output filtering, agent permission boundaries, MCP security, and continuous monitoring — integrated into your CI/CD pipeline.
24/7 AI threat monitoring, weekly automated red team runs, monthly posture reports, quarterly deep-dive assessments, and incident response.
Your AI product is your attack surface. We help you build secure-by-design LLM applications and prove their safety to enterprise customers and regulators.
Full OWASP Top 10 assessment of your AI product — architecture review, supply chain analysis, system prompt security, code-level vulnerability analysis, and enterprise readiness evaluation.
Multi-framework certification: Singapore AI Verify, EU AI Act conformity, NIST AI RMF alignment, ISO 42001 readiness — with audit-ready evidence packages and customer-facing trust docs.
Security-first AI development framework integrated into your engineering workflows — automated testing pipeline, pre-commit hooks, model evaluation framework, and security champion training.
National-scale AI safety testing, governance frameworks, and capacity building for government agencies deploying AI systems.
End-to-end national AI safety program: system inventory, centralized testing infrastructure (Moonshot, AI Verify), custom benchmarks, multilingual red teaming, and cross-agency compliance dashboards.
Comprehensive national AI governance framework adapted from Singapore Model AI Governance and EU AI Act requirements — customized for your legal and institutional context.
Specialized engagements for specific AI security needs — from MCP security to supply chain audits and custom benchmarks.
Security testing for Model Context Protocol server deployments — authentication, authorization, data isolation, scope enforcement, and trust boundary validation.
Audit your AI model supply chain — model provenance, dataset integrity, fine-tuning data validation, plugin/tool dependency scanning.
OWASP LLM Top 10 workshops, hands-on red teaming bootcamps, and AI-SDLC implementation training for your team.
Pre-negotiated response capability for AI security incidents. Threat hunting, forensic analysis, containment, regulatory notification support.
Domain-specific, jurisdiction-specific, or language-specific AI safety benchmarks with test dataset curation and platform integration.
Cross-framework mapping saves you from running separate compliance programs.
| Framework | Source | Coverage |
|---|---|---|
| OWASP Top 10 for LLM Applications (2025) | OWASP Foundation | 10 critical LLM vulnerability categories |
| OWASP Top 10 for Agentic Applications (2025) | OWASP Foundation | 10 critical agentic AI risk categories |
| AI Verify Testing Framework | Singapore IMDA / AI Verify Foundation | 11 governance principles |
| EU AI Act | European Commission | Risk-based AI regulation (2024–2027) |
| NIST AI Risk Management Framework | US NIST | Govern, Map, Measure, Manage |
| ISO 42001 | ISO | AI management system standard |
| MLCommons AI Safety Benchmarks | MLCommons | Standardized safety evaluation suites |
| MITRE ATLAS | MITRE | Adversarial Threat Landscape for AI Systems |