AI is transforming your industry and expanding your attack surface simultaneously. We help you navigate adoption with a security-first framework that keeps you compliant, defensible, and competitive.
We needed someone who understood both AI and security law. Cythelligence bridged that gap — they helped us build a governance framework that satisfied our legal team and our engineering team.
AI systems introduce a new category of risk: prompt injection, data poisoning, model exfiltration, and regulatory exposure. Our framework maps these risks against your specific AI footprint and builds controls that are proportionate and practical — not theoretical checklists that gather dust.
Systematic evaluation of your AI systems against emerging threat vectors: prompt injection, model theft, data poisoning, and output manipulation.
Policies, controls, and accountability structures for deploying and operating AI models responsibly across your teams and vendors.
Red-team assessment of prompt injection vulnerabilities in LLM-powered applications and agentic workflows before adversaries exploit them.
Evaluate training data practices, PII handling in AI pipelines, and demographic bias in model outputs against regulatory expectations.
Acceptable use policies, AI development standards, and third-party AI vendor risk requirements tailored to your sector and scale.
Gap analysis against EU AI Act, NIST AI RMF, DORA, and sector-specific AI regulations — with a practical remediation roadmap.
We sit at the crossroads of AI innovation and cybersecurity. Our team includes AI security researchers and regulatory specialists who speak both languages fluently.
We approach AI systems the way an attacker would — probing for prompt injection, data leakage, and model abuse before your adversaries do. Defense starts with offense.
We monitor the evolving AI regulatory landscape and translate requirements into practical controls your teams can implement — not legal abstractions that stall progress.