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A Custom AI Support Agent Built to Resolve 75% of E-Commerce Tickets

How we deploy an AI support agent that handles order queries, returns and FAQs autonomously.

Industry
E-Commerce
Timeline
4 Weeks
Built for
E-commerce brands

01 — Challenge

The problem

A fast-growing e-commerce brand processing 500+ orders per day typically receives 80–120 support tickets daily — the majority covering the same five topics: order status, delivery delays, return requests, product questions, and discount codes. Each ticket takes a support agent 8–12 minutes to handle, and with a team of three, tickets regularly queue for 6–12 hours before getting a response.

Customer satisfaction scores suffer, the support team burns out on repetitive queries, and scaling the team to keep pace with order volume is unsustainable. Off-the-shelf chatbots tend to fail here — they frustrate customers with rigid decision trees and can't access live order data.

02 — Solution

How we build it

We build a custom AI support agent using the Anthropic Claude API, connected directly to the brand's Shopify store and order management system via API integrations. The agent has real-time access to order status, shipping tracking, return eligibility, and product inventory — so it can give customers accurate, personalised answers rather than generic responses.

The agent handles the full resolution flow for tier-1 queries: it looks up the order, checks status, initiates returns if eligible, and sends confirmation emails — all without human involvement. For complex edge cases (damaged items, fraud flags, VIP customers), it escalates to a human agent with a full context summary so the handoff is seamless.

We build a monitoring dashboard showing deflection rate, resolution time, escalation reasons, and CSAT scores — so the team can continuously improve the agent's responses based on real data.

Stack & scope

  • AI Agent
  • Claude API
  • Shopify Integration
  • Customer Support Automation
  • NLP
Related service · 01AI EngineeringAI products, agents, RAG and automation shipped to production with evals and guardrails.

Next step

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