AI Security, from employees to agents.
AI adoption has outpaced the controls built for the pre-AI world. We help you discover, protect, and govern every AI interaction — from staff using copilots to autonomous agents calling your tools.
Discuss AI SecurityWhy now
Your AI footprint is bigger than your inventory.
Browser-based assistants, embedded copilots, in-house AI apps and autonomous agents each create exposure that traditional security tooling was not designed to see. We focus on three areas that need guardrails.
Secure every layer
Workforce. Applications. Agents.
Workforce AI use
Find shadow AI across browsers, SaaS apps and copilots, detect sensitive data pasted into prompts, and apply data-loss controls before information leaves your control.
AI applications
Protect model inputs and outputs at the application edge against prompt injection, jailbreaks and data exfiltration, so your AI-powered products behave as intended.
AI agents
Control tool calls, file access and privileges. Block unsafe autonomy and contain runaway loops and cost-abuse before they become incidents.
How we approach it
Discover, protect, govern.
Discover
Map where AI is used across people, applications and agents, including tools nobody approved.
Protect
Put guardrails in place against prompt injection, data leakage, harmful outputs and unsafe agent behaviour.
Govern
Apply consistent policy with audit trails and the reporting your compliance and leadership teams need.
What we deliver
Five engagements, scoped to your AI maturity.
- Workforce AI security
- AI application security
- AI agent runtime security
- AI red teaming & assessment
- AI infrastructure security
FAQ
Common questions
How do we manage AI security risk?
Start by discovering where AI is used, then protect the data and behaviour at each layer, and govern it with policy, audit and reporting.
How is AI security different from traditional cybersecurity?
AI systems take natural-language input and act on it, so attacks such as prompt injection and model manipulation bypass controls built for code, network and endpoint threats.
What is agentic AI security?
It governs what autonomous agents may do: which tools they call, which files and systems they reach, and how far their autonomy extends.
How do you protect data used with AI?
By detecting sensitive content in prompts and outputs, enforcing data-loss policies, and limiting what models and agents can access.
What is AI red teaming?
Controlled adversarial testing of your models, applications and agents to find jailbreaks, leakage and abuse paths before attackers do.
Get started
Ready to adopt AI safely?
Tell us how AI is used in your organisation today. We will come back with a scoped plan.