An AI support agent that cut tickets by 70% for a fast-growing e-commerce brand

The client's customer base was expanding faster than its support operation. Every new cohort of buyers produced the same questions, where is my order, how do I return this, when is the refund due, and every one of them landed on a human agent. Response times stretched, peak hours became inconsistent, and support cost grew in step with sales instead of behind them.

The agent had to answer from the client's real order, returns, and refund data, not from generic scripts. It had to hand a conversation to a human cleanly when it reached the edge of what it should decide. It had to work inside the existing CRM, helpdesk, and e-commerce platform rather than replace them. And it had to hold up during promotional peaks, when volume spiked hardest.

An AI-powered support agent that resolves queries instantly in natural conversation: order tracking, returns, refunds, and frequently asked questions are handled end to end without an agent. Behind it, intelligent ticket categorisation and priority routing send the remaining cases to the right person with context attached. A real-time analytics layer shows conversation volumes, resolution rates, and agent performance.

Conversational layer built on natural language processing; integrations with the client's CRM, helpdesk, and e-commerce platform for live order, return, and refund data; a routing service that classifies and prioritises tickets; an analytics dashboard over all interactions.

Discovery mapped the top query types and their data sources. Scope fixed the automation boundary, what the agent decides and what it escalates. Design covered conversation flows and handoff. Build integrated the platforms and trained the agent on real cases; weekly demos used live transcripts. Verification tested peak-hour loads and escalation paths before release. Run added the analytics review cadence with the support lead.

Routine inquiries stopped reaching the queue. Agents moved to complex cases, service scaled through peak demand without proportional hiring, and customers got consistent answers at any hour. The client reported stronger loyalty and retention as response times fell.

Automation is only trusted when the escalation path is impeccable. Every AI agent we build now ships with the human handoff designed first, and with analytics the support lead actually reads.