Manual PIM reviews don't scale. WatchTower PIM Coach uses AI to analyze every activation, identify behavioral patterns, and generate personalized coaching recommendations automatically.
Your security team can't review every PIM activation. Patterns get missed. Bad habits go unnoticed until something breaks. You need automation that thinks.
"Same justification 70 times this month." "Always requests max duration." "Uses Owner when Reader is available." Patterns humans don't notice.
Hundreds of activations per week. No way to review them all manually. Most organizations just hope nothing bad happens.
PIM portal shows activations. Log Analytics shows events. But nothing tells you what patterns mean or what to do about them.
Not just dashboards. AI that analyzes behavior, identifies patterns, and generates actionable recommendations.
AI identifies patterns across all activations: repeated justifications, duration habits, timing anomalies, role selection trends. Catches what humans miss.
Each user gets specific, actionable recommendations: "Request 2 hours instead of 8", "Include ticket number", "Consider Reader role instead of Contributor".
No manual effort. AI analyzes every activation, scores every user, generates every report. Runs automatically, forever, after setup.
AI understands context. Knows what roles were available when someone activated. Scores based on whether they made good choices, not just what they did.
One-time setup. AI runs forever. No subscription required.
Full AI-powered coaching system deployed to your Azure environment.
The system uses rule-based intelligence combined with pattern recognition. It analyzes activation data to identify behavioral patterns and generates recommendations based on best practices. Simple, explainable AI that produces consistent results.
No. Everything runs in your Azure environment. The AI logic is deployed locally. No data is sent to external APIs or processed outside your tenant.
AI analyzes all activations looking for: repeated justifications, duration habits (always max), timing patterns (unusual hours), role selection patterns (never using lower roles). When patterns emerge, they're flagged in reports.
Recommendations are based on observable behavior compared to best practices. "You requested 8 hours but only used 15 minutes" is data, not interpretation. The AI suggests what to try next based on patterns.
Recommendations are guidance, not mandates. Security teams review AI output and decide what to action. The system surfaces patterns - humans decide what to do about them.
No. It augments your team by handling the volume they can't. AI does the pattern detection at scale. Your team reviews high-signal findings and makes decisions. Humans stay in control.
No black box. Every recommendation has a clear reason. "You used Owner 12 times when Reader was available" - observable, actionable.
Delivered by a Microsoft MVP with deep expertise in Entra ID, privileged access management, and identity governance.
All AI runs in your environment. No external API calls. No data leaves your tenant. Secure by design.
Manual reviews don't scale. AI-powered pattern detection catches what humans miss and generates recommendations automatically.
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