An AI customer support agent answers customer questions on chat, WhatsApp and email. Unlike a FAQ bot, the agent connects to your systems. The agent checks an order, changes a booking or opens a ticket, then replies with the result.
Start with your ticket data
Your past tickets show where an agent helps most. Export the last three months of support conversations and group them by topic. Sort the topics by volume. The top five topics are your first scope.
Decide what the agent does
Split your topics into three groups:
- Answer only. Policies, opening hours, product details. The agent answers from your knowledge base.
- Look up. Order status, delivery date, booking details. The agent calls a read-only tool.
- Act. Change an address, cancel a booking, start a return. The agent calls a write tool and asks the customer to confirm first.
Keep large refunds, complaints and legal questions with your team.
Connect your systems
Each action needs a tool. A tool is a small, specific function with clear inputs and outputs:
get_order_status(order_id)update_delivery_address(order_id, address)create_return(order_id, reason)create_ticket(summary, priority)
Every tool checks the customer's identity and permissions before running. Give the agent the fewest tools possible for the job.
Write the knowledge base
The agent answers from the information you give. Write short, factual entries for each policy and product. Include exact wording for sensitive topics such as refunds. Review the entries every month, and update them the same day a policy changes.
Design the handover
A good handover keeps customers happy. Hand the chat to a person when:
- The customer asks for a person.
- The customer repeats the same question twice.
- The topic sits outside the agent's scope.
- An action fails.
Pass a summary with each handover: customer name, order number, the question and the steps the agent already tried. Your team starts with full context instead of asking again.
Pick your channels
Start where most of your volume comes from. In India and the Gulf, WhatsApp often comes first. Read how to build a WhatsApp AI agent for the platform rules. Website chat and email follow with the same agent and the same tools.
Measure the results
Track five numbers from day one:
| Metric | What the metric tells you |
|---|---|
| Resolution rate | Share of chats the agent closes without a person |
| Handover rate | Share of chats passed to your team |
| First response time | Seconds until the customer gets a reply |
| Customer rating | Satisfaction score after each chat |
| Cost per conversation | AI usage and hosting divided by chat volume |
Review a sample of conversations every week. Fix wrong answers in the knowledge base and add tools for repeat handover reasons.
Rollout plan
- Week 1: answer-only topics on one channel, during office hours.
- Week 2: add read-only lookups.
- Week 3: add actions with confirmation.
- Week 4: extend to 24/7 and a second channel.
Adjust the pace to your results. Move to the next stage once the resolution rate holds steady and customer ratings stay high.
Need a support agent built and connected to your systems? Our AI agent development team handles the full setup. Read What are AI agents? for the basics.