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Engineer security into your AI and GenAI systems: guardrails and AI firewalling, prompt-injection and data-leakage defences, model and pipeline protection, and secure integration of agents and copilots.
Our AI Security service designs and implements the controls that protect AI and GenAI systems across their lifecycle. We map your AI use cases, models, agents, data flows and integrations, threat-model them against frameworks such as the OWASP Top 10 for LLM Applications and MITRE ATLAS, and then engineer preventative controls — input/output guardrails, AI firewalling, prompt-injection and data-leakage defences, model and pipeline protection, and least-privilege agent design — integrated with monitoring and your existing security stack. The service secures AI you build, AI you buy and AI embedded in third-party products.
Yes, often more so. Copilots and embedded AI can read and act on your data with permissions you did not tightly scope. This service secures AI you build, AI you buy and AI embedded in products you use, focusing on guardrails, data protection and least-privilege integration.
Prompt injection is when attacker-controlled content manipulates an AI system into ignoring its instructions or performing unintended actions, including through indirect content such as a document or web page the model reads. For agents with access to tools and data, this can lead to data leakage or unauthorised actions, which is why inbound guardrails and least-privilege design are central to this service.
This service is implementation-focused: it engineers and deploys durable AI security controls. It complements point-in-time AI Security Assessments, and assessment findings are an ideal input into the controls we build.
Guardrails are designed and tuned to balance protection with performance and usefulness. We validate them against your use cases so that legitimate interactions are preserved while malicious or unsafe ones are caught.
We apply controls across the flow — access-controlled retrieval sources, outbound inspection for data leakage, and secure handling of prompts, responses and training data — so sensitive information is not exposed through AI interactions.
Yes. The controls and evidence support responsible-AI and governance requirements and can be aligned with standards such as ISO/IEC 42001 and the NIST AI Risk Management Framework.
Protect your organization with enterprise-grade cybersecurity, cloud, and managed IT solutions tailored to your business needs.
