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About QL Security

QL Security is a UK AI Security partner helping mid-sized organisations in regulated markets take control of their AI risk. We work with NHS trusts, local authorities, and professional services firms to assess exposure, implement working controls, and provide ongoing assurance that AI systems remain secure and compliant. We launched in 2026 to address a gap in the market: organisations adopting AI tools at pace, but without the governance, visibility, or technical controls to manage the risks that come with them. Most providers offer frameworks and reports. We deliver the actual controls - configured, tested and operating in your environment. Our work spans three core areas. Shadow AI discovery gives organisations visibility into the AI tools already in use across their workforce, including unapproved applications and data flows that existing security tooling cannot detect. LLM guardrails implementation protects organisations deploying large language models by establishing input and output controls, prompt injection defences, and behavioural monitoring. AI governance programme delivery supports boards and security teams in building the policies, risk frameworks, and audit trails required under the UK AI Act, DSPT, and emerging public sector AI standards. We are an AI Security partner and not just a consultancy. That distinction matters. Our engagements are defined by implementation outcomes, not report delivery. Clients receive working controls and documented evidence of assurance. QL Security holds Cyber Essentials certification and operates under ISO 27001-aligned practices. We understand the procurement, compliance, and risk environments of UK regulated sectors, and we design our engagements to fit within them. To find out whether we are the right fit for your organisation, visit https://qlsecurity.co.uk/

Services

Capabilities listed on this profile.

AI ConsultingCybersecurityAI AgentsAI DevelopmentGenerative AI

Team & locations

Stamford, England2 - 9 employeesFounded 2025More agencies here →

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