- AI tools were already in use, but access decisions varied by team and manager, creating inconsistent enforcement.
- There was no clear ownership for approving AI usage tied to sensitive workflows or data.
- Reviews focused on visibility, not on whether AI usage aligned with internal policies or risk tolerance.
CloudEagle Enabled Secure and Auditable AI Adoption Across Teams
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“Once AI adoption accelerated across teams, visibility alone wasn’t enough. We needed clear rules around who could use AI tools, under what conditions, and how those decisions were enforced and reviewed. CloudEagle helped us move from ad-hoc approvals to structured, defensible AI governance.”
~ Aditya Khosla, CTO, Iterative Health
12,000+
AI usage signals
1,500+
Policy decisions enforced
Always-on
AI governance
12,000+
AI usage signals
1,500+
Policy decisions enforced
Always-on
AI governance
Challenge
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Solution
- CloudEagle.ai was used to apply policy-based controls to AI tool access across teams.
- AI access was governed by role, purpose, and approval context rather than informal decisions.
- Automated reviews ensured AI usage stayed aligned with internal governance rules as teams scaled adoption.
Result
- AI usage decisions became consistent, traceable, and policy-aligned across the organization.
- Clear accountability emerged for who approved AI access and under what conditions.
- Leadership gained confidence that AI adoption followed defined governance standards.
Challenge
"AI tools spread quickly across our teams, but access decisions varied by role, manager, and function. Approvals often happened informally, leading to inconsistent enforcement across the organization.
Although policies existed, we enforced them manually and after the fact. Our security and legal teams struggled to clearly answer leadership questions about which AI tools were in use, who had access, and whether usage aligned with our risk tolerance."
Solution
- CloudEagle.ai applied policy-based governance across approved AI tools.
- AI access followed role, purpose, and data sensitivity, not ad-hoc approvals.
- Real-time controls blocked unauthorized or policy-violating AI access.
- Automated reviews ensured AI usage stayed aligned as adoption scaled.
- Tracked how Copilot and other AI tools were actually used across teams
Why CloudEagle.ai?
Iterative Health evaluated several solutions but chose CloudEagle.ai for four key reasons:
- Enforced AI usage policies across teams instead of relying on manual reviews.
- Blocked unauthorized or non-compliant AI access in real time.
- Tracked AI access decisions with clear ownership and approval context.
- Maintained consistent, audit-ready AI governance as adoption scaled.
Impact
Eliminating Shadow AI Tools
- Surfaced AI tools adopted without formal review
- Identified overlapping and high-risk AI usage early
- Ensured only approved AI applications remained active
- Validated Copilot rollout through adoption and access tracking
Time Saved and Governance Simplified
- Replaced manual audits and spreadsheets with automation
- Centralized AI access, usage, and ownership visibility
- Reduced time spent chasing approvals and visibility gaps
- Shifted IT focus from administration to policy enforcement
Risk Reduction and Better Control
- Flagged unauthorized or non-compliant AI usage in real time
- Reduced exposure to data leakage and compliance gaps
- Enforced consistent access policies across teams
- Gave leadership confidence in controlled, compliant AI rollouts
The Transformation
Before CloudEagle
No clear view of AI tools in use across teams, creating blind spots in governance
Teams relied on manual checks to understand who accessed AI applications
Security discovered unsanctioned AI tools late, often during reviews or audits
No continuous monitoring of AI access, usage, or policy violations
Governance stayed reactive instead of proactive
After CloudEagle
Full visibility into AI-enabled applications within minutes of onboarding
Automated discovery of sanctioned and unsanctioned AI tools across the stack
Continuous access monitoring replaced spreadsheet-based AI reviews
Real-time alerts flagged risky or non-compliant AI usage early
Teams enforced AI governance consistently without slowing innovation
