Traditional workflows take 5–6 weeks of manual triage and verification. We deliver confirmed exploits in 2–3 weeks, with proof that teams can act on.
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Noise reduction
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Weeks saved
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False positives on exploits
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Environment mapped
Engineering-led AI security for agentic systems
The Chaleit Difference
Many treat AI as a shortcut, not a strategic enabler. This leads to surface-level security testing that ignores the complexity of AI systems, where real risks come from how decisions are made, chained, and acted upon — not just from code or configuration.
We close that gap with engineering depth. Because we design and integrate agentic systems ourselves, we understand the unintended consequences of their interactions, including how agentic contracts define behaviour, guardrails, and boundaries. By combining private local LLMs with automated exploitation and expert security engineering, we stress-test your entire stack under real-world conditions.
We target the decision-making core of your AI. Instead of basic prompt testing, we simulate sophisticated attacks on system logic, data flows, and agent interactions, reflecting how attackers engage with AI systems. This results in actionable exploits and a clear, risk-based plan to fix your most critical vulnerabilities first.
Proven exploitation testing
Every critical finding includes working exploits and visual evidence. If we can’t demonstrate exploitation, we don’t report it as critical.
Context-aware analysis
Our private, local LLMs analyse AI apps in their full architectural context. This delivers near-zero false positives, threat-category grouping, and actionable reports.
AI-native offensive expertise
AI is never a black box to us. We build, integrate, and orchestrate agentic systems ourselves — a builder’s perspective that allows us to exploit and secure the risks others miss.
Multi-model, private by design
We assess AI systems across commercial and self-hosted models, with all analysis running in your environment. Your code and data stay under your control.
Focus on AI foundations
AI pressure-tests the systems you already have
AI doesn't introduce new problems in isolation. It accelerates the ones you already have.
With agentic AI, the risk increases. You're no longer testing static systems, but decision-making chains, agent interactions, and loosely defined guardrails, often governed by implicit or poorly defined contracts that shape behaviour and control outcomes.
Most organisations struggle not because AI is new, but because it sits on foundations that were never clearly understood or properly controlled.
Before adding more AI capability, the priority is to stabilise and strengthen what already exists. That’s where our Cyber Security Uplift work comes in. When secured properly, these systems enable faster decisions, safer automation, and more resilient operations.
AI Security Toolbox
Applied AI security across code, cloud, and context
AI Security Outcomes
Real assessments. Real exploits. Measurable savings.
Meet your cyber partners
Friendly faces, fierce defenders.