A 4,000-person European insurer facing imminent EU AI Act review couldn't answer the one question regulators would ask first: where are your high-risk AI systems, and how can you prove control? AIBound's Shadow AI Queue answered it in 24 hours — and built the continuous evidence trail the EU AI Act requires.
The EU AI Act doesn't ask whether AI exists in your organization — it asks whether you can prove control over it. This insurer couldn't. Security had point solutions, governance had spreadsheets, and nobody had visibility into thousands of unmanaged AI interactions happening outside official channels.
Using agentless API integrations, AIBound created a complete enterprise-wide inventory — not browser-only telemetry or manually maintained registries. Within 24 hours: a live inventory of 3,500+ AI applications and dozens of systems flagged for immediate EU AI Act-level review.
The EU AI Act expects traceability, logging, transparency, and ongoing monitoring — not a point-in-time snapshot. AIBound translated raw discovery into that operational governance layer. Every discovered AI system was automatically categorized: what data it could access, which identities interacted with it, whether CVEs or active exposure indicators existed, and where usage originated — giving GRC teams the evidence chain auditors would demand.
AIBound connected through agentless API integrations and built a live, enterprise-wide AI inventory rather than a browser-only snapshot or a manually maintained registry. Every discovered system was automatically categorized by data access, identity interaction, exposure indicators, and usage origin, then routed into a review queue where enforcement fires when risk exceeds policy.
AIBound continuously discovered AI agents, MCP servers, SaaS apps, browser extensions, and emerging services — surfacing what no manual registry or browser-only tool would capture.
Every system mapped to interacting identities, providing the EU AI Act's required traceability: not just what AI existed, but who used it and at what access level.
AIBound contextualized what data each AI system could reach and whether extensions amplified scope — enabling immediate prioritization of regulatory exposure.
Active CVEs, exposure indicators, and supply chain risks cross-referenced against every system automatically — no manual triage required before escalation.
Every system moved through defined review states: approved, pending, or blocked. Where risk exceeded policy, enforcement — block, restrict, remove — fired automatically.
AIBound attributed every discovered system to the identities interacting with it, the data it could reach, and the business units it touched — EU AI Act-ready traceability across the full 4,000-person organization, segmented by risk level and governance status.
When audit preparation began, the insurer already had the complete operating history: AI inventory, high-risk systems, identity attribution, exposure context, remediation actions, approval status, and governance records. Audit-ready weeks ahead of schedule — no spreadsheets, no screenshots, no scramble.
Many vendors answer where shadow AI is. AIBound answers what is high-risk, who is using it, what data it can access, what action was taken, and how we prove it — then enforces automatically when risk exceeds policy.
3,500+ AI applications discovered in 24 hours via agentless API integrations — agents, MCP servers, SaaS apps, and extensions. No browser telemetry. No manual registry.
Traceability, identity attribution, CVE records, remediation history, and governance records generated continuously — the exact evidence chain EU AI Act auditors require.
Where risk exceeded policy, enforcement fired automatically — block, restrict, or remove — with the action itself recorded as audit evidence.
"We couldn't answer the questions we knew regulators were going to ask: where are our high risks, and can you prove control? AIBound answered it in 24 hours and gave us the evidence trail."
— CISO, European Insurance Group
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