Adopt AI fast.Keep control of it.
An expert, evidence-based view of where AI is putting your data at risk, shadow AI, data leakage, access, vendors and controls, with a prioritised 30/60/90-day plan, and the team to fix it. In two to three weeks, not two quarters.
AI is moving faster than your governance can.
Employees adopt tools before anyone reviews them. Sensitive data ends up in prompts. Copilot surfaces over-shared files. AI vendors slip through without a security review. Most teams have no shared model for what's actually allowed, and no real visibility into what's already happening.
One assessment. Then we stay to fix it.
A land-and-expand model. The assessment proves where you stand; implementation deploys the controls; the retainer keeps you ready as AI keeps shifting.
Assessment
An expert readiness review across six workstreams. You walk away with an AI tool inventory, a prioritised risk register and a 30/60/90-day roadmap.
Implementation
We deploy the controls the assessment calls for: SASE/SSE configuration, MCP & agent governance, DLP, identity and access, plus admin enablement.
Retainer
AI risk doesn't stand still. Quarterly vendor reviews, policy updates, a training cadence and incident-response readiness on a monthly retainer.
Where AI puts you at risk, and how to close the gaps.
Delivered in 2–3 weeks: kickoff and discovery, risk scoring and analysis, then a final report and executive readout.
AI Usage Discovery
Surface every approved and shadow AI tool in use, by department, by use case, and the risks hiding in browser extensions and SaaS add-ons.
Data Leakage & Privacy
Map where customer data, employee records, source code, contracts and financials can leak through prompts, pastes and uploads.
Identity & Access Readiness
Review SSO, MFA, group permissions, guest access and over-shared documents before Copilot and internal AI surface them to the wrong people.
AI Vendor Risk
Score vendors against data retention, model training, logging, admin controls, certifications and contractual terms, consistently, every time.
Governance & Policy
Assess policies, ownership, approval workflows and employee guidance against a defensible model your legal and compliance teams can stand behind.
Controls & Monitoring
Test your real ability to block, allow, detect, log and respond to risky AI usage, not the policy on paper, the controls in production.
What "AI without guardrails" actually looks like.
Two of the most common ways AI leaks data, a chatbot that overshares, and an agent that over-reaches through MCP. Trigger the attacks, then flip the security controls on and watch the same attacks get blocked.
We don't just deploy on Cloudflare. We know it cold.
Our security work is built around Cloudflare's Zero Trust stack, and we implement it daily. One vendor, edge-grade enforcement, and controls that sit inline in front of your AI, not bolted on after the fact.
- Zero Trust & Access, identity-aware access to AI tools and data
- SASE / SSE, inline control over how staff reach AI
- DLP at the edge, stop sensitive data reaching prompts
- Workers & Pages, custom gateways and policy logic
- Workers AI & agents, governed AI you can actually audit
- Logging & monitoring, every AI request visible and retained
Built on evidence, not a product pitch.
Most AI security advice comes from integrators selling you their box. We start with a defensible, evidence-based view of what's actually at risk and why, then we stay to fix it. Faster than a Big-4, a fraction of the cost, and genuinely vendor-agnostic.
The first big public AI incident changes everything.
Shadow AI is already storing, and training on, corporate data. The window to get governance in place is before the incident, not after.
of IT leaders say employees adopt AI tools before security can even assess them.
of breached organisations had no AI governance policy in place.
of employees admit putting information into AI tools without approval.