Category: AI Incident Management
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How to Adopt Frank in 6 Weeks (Without Disrupting Your Team) You’ve read the case. You see the math. Now the question is: what does it actually take to deploy Frank? Here’s the 6-week path we use with every customer — assessment to go-live — and the risks we plan around. By Shawn Ennis•July 6,…
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How $50K Saves $1.16M (And Defers 6 Hires) I’m going to skip the prose and give you the math. Three deployment scenarios. Hard numbers. The payback in every realistic case is under three weeks. Here’s the business case your CFO will read. By Shawn Ennis•June 29, 2026•5 min read In the last four posts, I…
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4 Real Support Scenarios — And How Frank Handled Each One Theory is one thing. Watching an AI agent handle real tickets from your production support desk is another. Here are four scenarios from Rapax’s own support queue — and exactly how Frank responded. By Shawn Ennis•June 22, 2026•6 min read In the last post,…
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Meet Frank — The AI Tier 1 Agent Built for Telecom Frank is an AI-native support agent that lives inside your incident management system. He answers questions, classifies tickets, validates intake, catches false alarms, and escalates the rest — all grounded in your knowledge base. No hallucinations. Already in production. Here’s what he actually does.…
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The Hidden Cost of Tier 1 Triage (And Why Hiring Won’t Fix It) Every CFO has approved the same headcount request: “We need two more support engineers to handle the load.” Then six months later, the same request comes back. Here’s why hiring is the wrong lever — and what to do instead. By Shawn…
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Your Support Team Isn’t Broken — It’s Drowning Industry data shows 60–70% of support tickets aren’t actually problems. They’re knowledge base questions, incomplete reports, false alarms, and duplicates. Your six-figure engineers are spending 2–3 hours a day on triage work that shouldn’t require their skills. Here’s the math. By Shawn Ennis•June 1, 2026•5 min read…