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Reload the pageReal-world results from organizations that replaced ungoverned AI with a secure, compliant platform. From healthcare to financial services to legal, see the measurable impact of AI governance done right.
87%
Shadow AI Reduction
94%
Faster Audits
<2 Week
Deployment
Design target: 80%+
Shadow AI Reduction
Design target: 0
HIPAA Incidents
Design target: 1-2 weeks
Deployment Time
Design target: 90%+ faster
Audit Prep Time
Clinical staff using unapproved AI tools with PHI data
Areebi deployed with HIPAA-aligned policies across all departments
Design target: 4-8 weeks
Compliance Timeline
Design target: $300K+/year
Cost Savings
800+ capacity
AI Users Governed
Design target: 95%+ blocked
Policy Violations
OCC examiners flagging uncontrolled AI usage across trading and advisory
Areebi deployed with SOC 2 and PCI-DSS policy templates, workspace isolation for trading vs advisory
Design target: 0
Confidentiality Breaches
Design target: 80%+
Attorney Adoption
Design target: 3x faster
Document Processing
Capacity: 2,400+
Matters Protected
Attorneys using ChatGPT for contract analysis, risking client privilege
Areebi deployed with client-matter isolation, PII masking for all legal documents
Design target: 100%
NIST AI RMF Coverage
On-premise
Deployment Model
1,500+
AI Users (capacity)
Automated by design
OMB Reporting
Executive Order 14110 mandate to deploy AI with governance, within existing FedRAMP authority
Areebi deployed on-premise within FedRAMP boundary, NIST AI RMF policies configured
Design target: 1-2 weeks
Time to Deploy
Typical: 15-30 tools
Shadow AI Discovered
$30K (Secure Essentials)
Annual Cost
Design target: 70%+
Risk Score Improvement
Growing AI usage across engineering, marketing, support with no visibility or controls
Areebi's Secure Essentials tier deployed in days, covering all teams
Design target: 100%
FERPA PII Detection
12+
Campuses Governed (capacity)
Typical: 30-50
Shadow AI Tools Surfaced
Design target: 2-4 weeks
Full Deployment
Faculty and staff using dozens of AI tools without oversight, with FERPA-protected student records being pasted into public AI tools
Deployed Areebi with student record DLP detection, campus-level workspace isolation, and FERPA-specific compliance templates
“Before AI governance, we had no idea how many faculty were pasting student records into ChatGPT. A governed AI environment with FERPA-aware DLP is what allows higher-education institutions to demonstrate compliance with the same diligence they apply to every other student-data system.”
- Representative voice: CISO in a multi-campus higher-education system (illustrative, no real customer)
Design target: 0
IP Leakage Incidents
Design target: 90%+
Engineer Adoption
Design target: 3-5x
Faster Design Reviews
Design target: 100%
ITAR Coverage
Engineering teams using AI for design optimization can inadvertently share ITAR-controlled CAD specifications and trade secrets, with no DLP coverage for AI channels
Areebi deployed with custom DLP patterns for engineering nomenclature, ITAR-aware data classifiers aligned to the United States Munitions List, and workspace isolation per business unit
“Engineering teams want to use AI. We cannot risk exposing ITAR-controlled designs. The combination of on-premise deployment, ITAR-aware DLP, and per-business-unit workspace isolation is what gives an aerospace and defence manufacturer the confidence to enable AI while keeping IP and export compliance airtight.”
- Representative voice: VP of Engineering in a global aerospace and defence manufacturer (illustrative, no real customer)
Design target: 2,000+/month
Secrets Intercepted
Design target: 75%+
Developer Adoption
Design target: 0
Source Code Exposures
Design target: < 50ms
DLP Latency
Developers using GitHub Copilot, ChatGPT, Claude, and other AI tools can share proprietary source code, API keys, and internal architecture details with no security visibility
Areebi deployed with source code pattern detection, API-key and secret scanning aligned to OWASP LLM06, and developer-specific workspace policies balancing security with productivity
“Engineering culture lives or dies on developer velocity. A governance layer that adds 30-50ms of latency and masks secrets in-line - rather than blocking the whole prompt - is what lets a security team enable AI-assisted development without becoming the team that breaks the IDE.”
- Representative voice: Head of Security in a Series C SaaS company (illustrative, no real customer)
Design target: 100%
Claims PII Protected
Design target: 40-60%
Faster Claims Processing
Design target: 0
Regulatory Findings (AI)
Design target: 3 of 3
NAIC Principles Coverage
Claims adjusters can expose policyholder PII through AI summarization, underwriting teams lack bias monitoring for AI-assisted risk scoring, and there is no audit trail for state DOI examiners
Areebi deployed with insurance-specific PII patterns, bias monitoring for underwriting workflows, and examiner-ready audit reports aligned to NAIC AI principles
“State examiners ask specifically about AI governance controls in market conduct exams now. Having an audit trail and bias monitoring reports ready, aligned to the NAIC AI principles, is what changes a carrier's regulatory posture from reactive to demonstrably compliant.”
- Representative voice: Chief Compliance Officer in a top-20 insurance carrier (illustrative, no real customer)
Join the organizations that have replaced ungoverned AI with a secure, compliant platform. See measurable results in your first 30 days.