The Problem You Already Know
It’s 9pm. A customer messages your WhatsApp asking about pricing. You’re having dinner with your family. By the time you reply tomorrow morning, they’ve already bought from your competitor who answered in 30 seconds.
This happens every night.
Hong Kong e-commerce data shows that 50-60% of customer inquiries arrive between 6pm and 9am. If you’re not responding instantly, you’re not just losing sales—you’re actively handing them to someone else.
The traditional solution? Hire night-shift staff. But at HK$18,000-22,000/month per customer service rep, that’s an expense most SMEs can’t justify.
There’s another way.
The Alternative: AI That Actually Works
Conversational AI isn’t the chatbot garbage from 2015 that frustrated everyone with “I don’t understand your question.” Modern AI agents, properly configured, can:
- Answer product questions using your actual catalog data
- Handle logistics queries by checking real-time shipping status
- Qualify leads based on criteria you define
- Escalate complex issues to a human—automatically, not randomly
The key phrase: properly configured.
Most AI projects fail not because the technology doesn’t work, but because companies try to build custom solutions from scratch. By the time it’s ready, the market has moved on.
Our approach is different. We don’t write code. We configure enterprise-grade AI frameworks and deploy in days, not months. You get a working system while your competitors are still in “requirements gathering.”
The Math: Why This Makes Sense
Let’s be specific about the numbers.
| Cost Factor | Hiring Night Staff | AI Agent |
|---|---|---|
| Monthly cost | HK$18,000-22,000 | ~HK$2,000-5,000 |
| Setup time | 2-4 weeks recruiting | 3-5 days deployment |
| Scalability | Linear (more staff = more cost) | Near-zero marginal cost |
| Sick days / turnover | Yes | No |
| Handles 3am inquiries | Only if you pay overtime | Always |
A properly deployed AI agent resolves 60-70% of routine inquiries without human involvement. That’s not replacing your customer service team—it’s freeing them to handle the 30% that actually needs human judgment.
What About Our Local Context?
Hong Kong customers message in a mix of English, Cantonese romanization, and shorthand. “Pls check tmr delivery” or “幾錢” followed by an English product name.
Generic chatbots trained on American English fail immediately.
We configure AI agents with semantic understanding—they interpret the intent behind a message, not just the words. The system doesn’t need perfect grammar; it needs to understand that “M gei order” means “I forgot my order details.”
This isn’t a selling point we lead with. It’s just table stakes for operating in Hong Kong.
Compliance: PDPO is Non-Negotiable
The Personal Data (Privacy) Ordinance applies to your AI just like it applies to your human staff.
We build compliance into the architecture:
- Transparency: Customers know they’re talking to an AI
- Data minimization: Sensitive information is redacted before storage
- Access controls: The AI can read your catalog but cannot modify orders without human approval
This isn’t optional. If your AI vendor can’t explain their PDPO compliance strategy, find another vendor.
Implementation: What Actually Happens
Here’s the realistic timeline for a typical SME deployment:
Day 1-2: Knowledge Base Setup We organize your existing materials—product PDFs, FAQ documents, pricing sheets—into a format the AI can reference.
Day 3-4: Configuration & Testing We configure the AI logic, set up escalation rules, and test against real scenarios (including edge cases).
Day 5: Go-Live with Safety Rails The system launches with human oversight. Complex or high-value queries still route to your team while the AI handles routine volume.
Week 2+: Optimization Based on real conversation data, we refine responses and expand capability.
No six-month development cycle. No massive upfront investment. You’re operational within a week.
Frequently Asked Questions
”Is this a monthly subscription that keeps going up?”
Unlike SaaS platforms that charge per seat, you own the configured asset. Ongoing costs are compute usage (typically HK$1,000-3,000/month depending on volume) plus optional maintenance.
”What if the AI gives wrong information?”
We implement retrieval-based answers—the AI pulls from your verified knowledge base, not the general internet. It can still make mistakes, which is why we keep humans in the loop for anything consequential.
”Can I try this before committing?”
Yes. We typically do a 48-hour proof-of-concept on your actual use case before any significant investment.
The Bottom Line
You’re already losing after-hours revenue. The question isn’t whether to automate—it’s how fast you can get there.
Some companies will spend six months building custom solutions. Others will subscribe to expensive per-seat SaaS and watch costs scale with headcount.
Or you can deploy a configured, enterprise-grade AI agent this week. Same outcome, fraction of the time.
That’s the integrator advantage.