AI Security & Governance | Enterprise AI Agent Security
Your AI Agents Are in Production. Is Anyone Securing Them?
Most security teams are still writing policies for AI while attackers are already exploiting it. We help organisations assess, architect, and harden AI agent deployments – from a single LLM integration to a fleet of production agents.
Built by practitioners who have governed 60+ production AI agents, evaluated 10+ AI security vendors, and built AI-native security tooling from scratch.
Built on real delivery. Not theory.
We did not learn AI security in a classroom. We built the architecture, ran the red team, evaluated the vendors, and shipped the tooling in a globally regulated online trading environment.
The problem
AI moves fast. Security has not caught up.
Every week, engineering teams ship new AI agents, LLM integrations, and agentic workflows into production. Most go live with no formal security review, no guardrails, no defined identity boundary, and no one watching for prompt injection or data exfiltration.
No security review gate
Most AI agents go from prototype to production without any security review. Architecture risks, permission over-scoping, and missing guardrails get shipped with the feature.
Existing tools cannot see this
Your SIEM, WAF, and vulnerability scanner were not built to detect prompt injection, jailbreaks, or LLM data exfiltration.
Agentic risk is systemic
One poorly scoped agent with access to internal APIs can become a pivot point across your entire stack.
Technical Assessments
Evidence-driven security assessments.
Red Team Assessment
Adversarial testing across network, application, identity, and cloud environments.
Delivered via CQ-AI Platform
View assessment ->Smart IoT Security
Security assessment for connected devices, smart building systems, and intelligent infrastructure.
Delivered via CQ-AI Platform
View assessment ->Purple Team
Collaborative attack-and-defend exercises to measure detection and response effectiveness.
Delivered via CQ-AI Platform
View assessment ->Cloud Assessment (AWS, Azure, GCP)
Cloud security posture review, IAM analysis, and compliance mapping across major cloud platforms.
Delivered via CQ-AI Platform
View assessment ->Standard Assessments
Structured vulnerability assessments and security reviews across applications and infrastructure.
Delivered via CQ-AI Platform
View assessment ->PCI-Based Segregation
Payment card environment segmentation design and compliance validation.
Delivered via CQ-AI Platform
View assessment ->CI/CD Security (DevSecOps)
Security integration into development pipelines including SAST, DAST, SCA, and secrets scanning.
Delivered via CQ-AI Platform
View assessment ->AI Security Flagship
AI security for production agent systems.
★ Agentic AI Security Assessment
Structured review of AI agents, LLM integrations, and agentic workflows against OWASP AI Security Top 10 and MITRE ATLAS.
Explore ->AI Infrastructure & Architecture Review
Architecture review of AI agent deployments against security standards, trust boundaries, identity design, and defence-in-depth patterns.
Explore ->AI Red Team
Adversarial testing for LLMs and AI agents: prompt injection, jailbreaks, multi-turn attacks, tool abuse, and data exfiltration.
Explore ->AI Security Gateway Evaluation & Implementation
Structured vendor evaluation and production deployment of AI security gateway controls.
Explore ->AI Security Operations Agents
Purpose-built AI security agents deployed in Slack or Microsoft Teams for threat hunting, triage, and response.
Explore ->AI security is different
This Is Not a Standard Penetration Test.
| Traditional Assessment | AI Security Assessment |
|---|---|
| Tests known vulnerability classes (CVEs, misconfigs) | Tests AI-specific attack surfaces (prompt injection, jailbreaks, context poisoning) |
| Static – tests a point in time | Dynamic – AI agent behaviour changes with context and model updates |
| Tool-driven scanning | Requires human adversarial reasoning plus AI-assisted tooling |
| Scope: infrastructure, applications, APIs | Scope: models, prompts, agent logic, tool access, output validation |
| Pass/fail against known signatures | Nuanced risk – same prompt can succeed or fail depending on framing |
| Covered by most pentest firms | Genuinely specialist – most firms have never tested an AI agent |
Why us
We have done this in production. At scale.
ChelonIQ.AI was founded by practitioners who built and ran enterprise AI security programmes – not analysts who read about it.
Governed 60+ production AI agents end-to-end
Covering customer engagement, finance automation, compliance intelligence, and engineering, in a globally regulated fintech environment.
Ran a formal three-vendor gateway evaluation
14 attack categories, 300+ adversarial prompt test batteries, four hard evaluation gates, and production deployment of the winning solution.
Built AI-native security tooling from scratch
Autonomous code review and threat modelling agents, security architecture review agents, and AI-powered SOC tooling.
Blocked 16,500+ attack attempts
AI security gateway deployment in a production environment serving millions of users globally.
CISSP | CCSP | OSCP | OSCE | 12+ years across fintech, financial services, and enterprise security
Start with a conversation.
Every engagement begins with a free 30-minute discovery call.