Sha Tin sits in a regional context that genuinely changes the build. Connectivity assumptions, the rhythm of the working week, the proximity of your team to your customers - none of those are details our default AI chatbots template would catch.
AI customer support - wired into a Sha Tin workflow, not bolted on the side.
Our goal is to give Sha Tin businesses a three-day weekend, so people can spend more time with their families and the people they love :)
What AI chatbots actually does
Trained on your business, not Wikipedia. AI assistants that answer pricing, hours, availability, bookings - and escalate cleanly when the customer needs a human.
- 01 Trained on your documents, FAQs, and past tickets
- 02 Books appointments, takes deposits, qualifies leads
- 03 Live hand-off to a human when needed
- 04 Daily quality reports so you stay in control
Built on: Claude OpenAI Custom RAG pipelines
Without Kiwi Dynamics
With Kiwi Dynamics
What you actually get
Every engagement is scoped and quoted up front. This is what is in the box.
- A working pilot, in productionNot a prototype on someone's laptop. The first slice of AI chatbots runs against real work within weeks.
- Your data stays yoursIt runs on your accounts and your tools. If we part ways you keep the system and everything in it.
- The workflow mapped before codeWe write down what good looks like for Sha Tin businesses first, so nobody is guessing at handover.
- Support after it landsThe people who built it stay reachable when the business changes shape around it.
How AI chatbots compares
The two things most businesses do instead, and where each one runs out.
| Hiring for it | An off-the-shelf tool | Kiwi Dynamics | |
|---|---|---|---|
| Fit to how you work | Fits perfectly, costs a salary | You bend your process to suit the tool | Built around the workflow you already run |
| Time to something useful | Immediate, and permanent | Quick to switch on, slow to make fit | A working slice in weeks, then hardened |
| Who owns the data | You do | The vendor, on the vendor's terms | You do, in your own accounts |
| When it breaks | That person sorts it, if they are in | A support queue and a ticket number | The people who built it |
| What it costs | A salary, every year, forever | Per seat, forever, used or not | Scoped and quoted up front |
Our field notes from Sha Tin builds.
- Sha Tin anchors the New Territories' manufacturing, logistics and science park economy - AI here means industrial-scale operations work, not office admin.
- Hong Kong Science Park and a broad manufacturing and logistics base serving cross-border trade with mainland China sit here. Businesses want AI that handles scheduling, compliance and cross-border logistics without becoming the bottleneck.
We work with teams across Sha Tin: Science Park · Tai Wai · Fo Tan · Ma On Shan.
Talk to us about this →
How we build AI chatbots for a Sha Tin team.
We scope narrow, ship a working pilot, then harden it into production. The first slice is the highest-leverage workflow for your Sha Tin business, so value lands before the build is finished. AI customer support.
Talk to usHow the work runs
- Find the one workflowWe look for the job costing Sha Tin businesses the most hours or the most leads, and deliberately ignore the rest for now.
- Ship a working sliceA narrow version goes into production in weeks, against real work, so the value shows up before the build is finished.
- Prove it, then widenWe measure it against what the work cost before. If it does not pay for itself, we say so rather than scaling it.
- Harden and hand overLogging, fallbacks and a real handover, so it keeps running when we are not in the room.
The outcome for Sha Tin teams
What changes for Sha Tin teams after this lands: the work that used to need a person stays done, the work that needs a person gets done with their attention undivided. Handles 60-70% of routine enquiries without human input.
Not your typical AI agency.
Honest about what AI can and cannot do
Ships the one workflow that pays for itself
Hours given back, never the size of the invoice
*Every engagement is scoped and quoted up front. Results vary by workflow and business.
FAQ
How fast could we have AI chatbots in production?
Eight to ten weeks for most Sha Tin businesses. Faster if your data is in good shape and slower if we're untangling a legacy integration first. We'll give you a realistic number on the scoping call rather than the optimistic one.
What's the smallest engagement you'd take on?
A two-week paid discovery for Sha Tin businesses that aren't sure whether the build is worth doing at all. You get a one-page write-up of what we'd build, what we'd skip, and what it would cost. About 30% of those discoveries end with us recommending you don't proceed.
Can you walk us through a comparable build?
Yes - on the first call we'll pick the closest engagement we've shipped to what you're describing and walk through the outcome, the headcount and the time it took. Handles 60-70% of routine enquiries without human input.
What if our Sha Tin doesn't have any data ready?
Most don't. Getting the data into shape - ingestion, cleaning, the lightweight contracts you need before any model is useful - is part of the engagement. For AI chatbots specifically, we typically run that work on Claude, OpenAI, Custom RAG pipelines and assume messy starting conditions from day one.
Twenty minutes, your call.
You describe what's broken. We'll tell you what we'd actually do about it.
Talk to us about this
Tell us what you're trying to do and we'll reply with how we'd build it - no obligation.