Run 24/7 Customer Support With AI Agent: Chin Hin Group Case Study

A customer’s ceiling fan is wobbling. They call customer support and wait 20 minutes on hold. When an agent finally picks up, the customer explains the whole issue — and the agent manually types every word into a system.

Frustrating for the customer. Exhausting for the agent. And completely preventable.

This is the problem Chin Hin put on the table: how do you transform after-sales support from a manual, reactive process into something that resolves issues instantly, 24/7, without a human touching a keyboard for routine cases?

Their framing was direct: service is the new sales. A customer whose issue gets fixed in 2 minutes comes back. A customer who waits 20 minutes and gets a callback that never arrives doesn’t.

The Three Ways Manual Support Fails

Chin Hin identified three specific breakdowns in their support operation. These aren’t unique to them — you’ll recognise at least one.

• The Admin Drain. Agents spend the bulk of their time logging calls and typing case notes. Not solving problems. Not helping customers. Just entering data that should be captured automatically. Every minute spent on data entry is a minute not spent resolving the next case in the queue.
• Repetitive Fatigue. Skilled support staff spend hours every day answering the same questions. “Where’s my warranty?” “Is this covered?” “How do I fix this error?” The same answers, over and over, to every new customer who calls. The knowledge is there — it’s just locked inside the heads of agents who have to repeat it manually every time.
• Follow-Up Failure. Without a system that tracks and flags cases automatically, critical issues fall through the gaps. A callback that doesn’t happen. An escalation that sits unactioned. An angry customer who gives up and doesn’t come back. When your team is managing cases by memory and spreadsheet, the ones that get attention are the ones making the most noise — not necessarily the ones that need it most.

The result: a support team that’s always behind, always reactive, and spending most of their time on work that follows a predictable script.

What a Team of Four Early-Career Digital Agents Built

Chin Hin didn’t hire a large agency to solve this. The challenge was handed to Team Fantastic Four — four early-career Digital Agents competing in a hackathon sprint. No enterprise consulting credentials. No prior experience with large-scale support systems. Just a clear brief, the right skills, and a defined window to deliver.

They built their solution around Fiamma’s appliance product catalog — brands like Elba, Faber, Tuscani, and Rubine — as the simulation context. And what they delivered in that sprint was a fully working AI Customer Success Guardian: an AI-powered support agent that handles the entire customer support process on its own, from the first message through to technician booking and spare parts compensation.

Not a chatbot that answers FAQs. An agent that takes actions, creates records, dispatches people, and resolves cases — without a human in the loop for anything routine.

How It Works: A Customer Support Scenario

The best way to understand what was built is to walk through what happens when a customer actually reaches out.

1. The customer contacts support about a wobbling ceiling fan.

The AI doesn’t open with a form. It acknowledges the problem, offers a quick troubleshooting tip based on the specific product manual, and in exchange for that tip, asks for the model number. Then it asks for the serial number to check warranty coverage. By the time the conversation gets to booking a technician, the AI already has everything it needs — without the customer feeling like they were put through an intake process.

Example: “That sounds like it could be a balancing issue. Let me pull up the troubleshooting guide for your model — can you share the model number so I can check the right steps for your unit?”

Every piece of information is gathered naturally, in exchange for something useful. No incomplete tickets. No agent needing to remember the checklist.

2. The AI gives exactly 3 troubleshooting steps.

Three steps, pulled from the product manual for that exact model. If the issue isn’t resolved within 5 minutes of the conversation starting, the AI stops troubleshooting and moves to booking a technician. Every session ends with a clear summary of what happened and what comes next.

Same quality of response every time — whether it’s Monday morning or Saturday night.

3. Warranty status is checked instantly.

The AI queries the warranty database in real time during the conversation. The customer gets a clear answer — covered, not covered, or expired — right then, without waiting for a callback.

If the product is under warranty, the technician visit is free. If not, the AI confirms charges apply before booking.

4. If a part is needed and out of stock, the system handles compensation automatically.

This is the follow-up failure point, solved. When a required part isn’t available, most support teams have no standard response. The AI Customer Success Guardian does.

It evaluates the customer’s situation and generates the appropriate offer:

• In-warranty and the failure is serious → 1-to-1 unit exchange
• Bought less than 7 days ago → Full refund
• Out of warranty → Loyalty discount voucher for a new unit

The customer picks their option in the chat. The voucher code or exchange confirmation is delivered in the same conversation. No supervisor approval. No callback. No manual processing.

5. Safety situations trigger immediate escalation.

Any mention of fire, smoke, sparks, burning smell, or electric shock stops the conversation. The AI tells the customer to unplug the appliance immediately and triggers an urgent technician dispatch — automatically, without waiting for an agent to make that call.

This isn’t judgment-dependent. It happens the same way, every time, regardless of who is working the queue.

What the Customer Support Manager Sees

While the AI handles customer conversations, the support team has a live view of everything happening.

A dashboard shows every active case, ticket status, technician assignments, and how customers are feeling in real time. The system tracks sentiment across every message — not just at the end of the call. If a customer’s frustration is escalating, a flag goes up before it becomes a complaint or a bad review.

This changes the manager’s job. Instead of monitoring individual calls and hoping nothing falls through the cracks, they oversee a system. The AI handles the volume. The team steps in for the cases that actually require human judgment — the complex ones, the sensitive ones, the high-value ones.

Chin Hin’s framing captures this exactly: freeing human agents to handle complex, high-value care — not repetitive questions and manual data entry.

The Pattern Across Malaysian Businesses

This isn’t an isolated outcome. The same approach plays out across industries.

• A fintech startup automated their most common customer inquiries and cut ticket resolution time by 52%. Their agents shifted from answering the same questions repeatedly to handling escalations that actually required judgment.
• An engineering company cut inquiry response time by 50% by automatically routing and qualifying leads before a human got involved.
• A retail brand significantly reduced the manual workload on content and posting by automating a process that had previously taken hours every week.

Same structure every time: a clear operational problem, a scoped sprint, early-career Digital Agents, documented handover. The business doesn’t just get a working tool — they get a system they own, understand, and can build on without going back to the team that built it.

Start Running 24/7 Customer Support

Every week your support team manually logs calls, answers the same warranty questions, and follows up on cases that should have been closed automatically — is a week a competitor is compounding their advantage.

The companies building these systems now aren’t doing it with large budgets or senior engineering teams. They’re doing it with focused talent, clear problem definitions, and time-boxed sprints. Four people. A defined brief. A few weeks of execution.

Team Fantastic Four built Chin Hin’s AI Customer Success Guardian in a hackathon sprint. It handles real support scenarios end-to-end — intake, troubleshooting, technician dispatch, spare parts compensation, sentiment escalation. The system, the documentation, and the handover were all delivered. Four people. One sprint. A production-ready system.

If your support team is still running on manual steps and inconsistent follow-ups, that’s not a people problem. It’s a system problem. And a system problem has a system solution.

Service is the new sales. A customer who gets their issue fixed in 2 minutes will buy from you again. A customer who waits 20 minutes and never gets a callback won’t. Build the system that delivers it consistently — not when an agent remembers to follow up.

Check out Kabel’s DXP to see how a Digital Agent team can build and deploy yours in 10 weeks.