Building an Escalation Root-Cause Agent with Gemini and ADK

Gen AI Academy APAC — Track 1 (AI Agents with Gemini, ADK, and Cloud Run) Why I built this I lead a customer service team of 25 agents at Amazon, handling both buyer-side and marketplace seller support. A big part of my job is reviewing escalated cases — calls or chats where a customer asked for a supervisor — and figuring out why they escalated in the first place. Was it a policy gap? A training issue? A system limitation nobody flagged? Right now, that review is manual. Every escalation gets read, tagged, and turned into a coaching note by a human — usually me, or one of my leads. It works, but it doesn't scale well, and patterns across dozens of cases are easy to miss when you're reviewing them one at a time between everything else on your plate. So for Track 1 of the Gen AI Academy APAC program, I built an agent that does the first pass of this analysis automatically: read an escalation summary, classify the root cause against a standard taxonomy, flag whether it looks like a repeat pattern, and draft a coaching note — the same way I would, just faster and more consistently. What it does The agent takes a case summary like this: Customer requested a refund for a damaged item outside the standard return window. Agent denied it citing policy; customer says a rep last month approved a similar exception for someone else. And returns a structured analysis: { "root_cause_category" : "policy_misapplication" , "severity" : "medium" , "is_likely_repeat_pattern" : true , "pattern_reasoning" : "Inconsistent policy application across agents suggests a training or documentation gap rather than an isolated error." , "coaching_note" : "..." } It's built on Google's Agent Development Kit (ADK) with Gemini as the underlying model, and deployed as a live service on Cloud Run . The agent has one tool — a lookup function for the standard root-cause taxonomy — which keeps the categories consistent and easy to update without touching the core prompt. For batch review, I also built a