What can an AI customer service agent handle?
It can handle common questions, status checks, routing, ticket creation, and basic troubleshooting when the answers are approved and the workflow is clear.
Customer support
AI Customer Service Agent
Answer common questions, route support requests, create tickets, and escalate customers with full context. Refract trains this agent on your workflow, approved knowledge, tools, and handoff rules so your team gets more coverage without losing control.
Who it helps
Built for the people already carrying this workflow.
Refract is designed to give teams more leverage, cleaner context, and more reliable follow-through. The agent handles the repeatable parts, while people stay involved where judgment matters.
- Customer service representatives
- Tier-1 support agents
- Call center agents
- Support specialists
Workflow
The work this agent can help move forward.
01
Answer frequent customer questions from approved knowledge
02
Look up order, account, or request status where systems allow
03
Create or update support tickets
04
Route customers by issue type, urgency, or account status
05
Capture a clear summary before human escalation
06
Follow support policies for refunds, cancellations, and exceptions
Sample scenario
See how it handles a real conversation.
A representative exchange — what the agent hears, what it asks, what it captures, and when it hands off to a person.
A customer calls at 9:15pm about an online order placed three days ago with no shipping update.
Caller
Hi, I ordered something three days ago and I haven't gotten a shipping update. I'm starting to get worried.
Agent
I can look into that. Can I get the email address on the account?
Caller
Sure, it's sarah@example.com.
Agent
Thanks. Your order shipped yesterday with UPS. I'm sending the tracking number to that email right now.
Caller
Oh good. Any idea when it'll arrive?
Agent
Estimated delivery is this Friday. If it doesn't arrive by end of day Friday, support would open a trace. Want me to flag your account now so the context is already there if you need to follow up?
Caller
Yeah, that would be great.
Agent
Done. A note is on your account with the order details and today's date. A rep can pull that up immediately if you call back.
Collected
- Account email
- Order status (shipped via UPS)
- Tracking sent to customer email
- Follow-up note added to account
Action taken
Sent tracking email. Added account note with order ID, shipping status, and expected delivery.
Outcome
Customer resolved at 9pm without waiting for business hours. Support starts the next day with the full context if a follow-up is needed.
Handoff rule
Would escalate immediately if the customer said the order was wrong, asked for a refund, or expressed frustration that continued after the first answer.
What improves
What gets better when this agent is running.
- Lower repetitive support volume
- Shorter wait times during busy periods
- Consistent answers from approved knowledge
- Better handoff context for support teams
Connections
System categories it connects to.
Help deskCRMKnowledge baseOrder systemAccount portalSlack or Teams
Specific integrations confirmed at scoping.
Controls
Guardrails that keep it useful.
- Approved support answers
- Account verification before sensitive information
- Escalation for frustrated or high-value customers
- Transcript review and quality scoring
FAQ
Questions teams ask before they deploy.
Can it escalate to a human support rep?
Yes. Refract supports warm handoff with a transcript, issue summary, collected details, and the reason the agent escalated.
How does it avoid giving wrong answers?
The agent answers from approved knowledge and follows a defined support flow. Sensitive claims, policy exceptions, or uncertain answers can be routed to a person.
Can it create tickets in our help desk?
Yes. Refract can create tickets or send structured handoff data to your help desk, CRM, email inbox, or webhook.
Is this better than a standard chatbot?
A standard chatbot often answers static questions. Refract is built for workflows: collect fields, call tools, route requests, and hand off with context.
Start here
Map one workflow before you expand the agent.
Bring the process, examples, routing rules, and systems this service needs to use. We will help you decide what should be automated, what should be escalated, and how to prove the first deployment.
Talk through your AI Customer Service Agent
Share the workflow, current bottleneck, and tools involved. We will follow up with a practical first-deployment path.