Customer Support Agent

The problem

Support queues grow faster than headcount. Engineers get pulled in. Senior people spend Friday mornings triaging tickets that could have been answered by a well-read document retriever.

Our approach

We build a RAG pipeline over your documentation, Zendesk ticket history, Confluence, and Notion. The agent handles L1/L2 tickets autonomously and escalates L3 with a structured handoff — what the customer asked, what was tried, what the agent found in the runbooks.

Sample timeline

1. 1

   Week 1–2

   Discovery — map ticket categories, identify top 20% by volume

2. 2

   Week 3–5

   RAG pipeline — ingest docs, tune retrieval, eval on historical tickets

3. 3

   Week 6–8

   Agent build — tool-use, escalation logic, handoff format

4. 4

   Week 9–10

   Production deploy — shadow mode, then live with rollback plan