We've worked with enough operators in Kwun Tong to know that the brief that arrives in our inbox is rarely the brief that ends up shipped. The first thing we do on any AI document processing project is sit with your team for a day before we propose anything.
For Kwun Tong operators who want a working pilot in weeks, not a year-long programme.
Our goal is to give Kwun Tong businesses a three-day weekend, so people can spend more time with their families and the people they love :)
What AI document processing actually does
Scanned invoices, signed contracts, handwritten timesheets, PDF specs - extracted into clean data and routed where they belong. No more typing what someone already wrote.
- 01 Vision models read scans, photos, and handwriting
- 02 Pushes structured data into Xero, your CRM, or sheets
- 03 Confidence flags route low-certainty docs to a human
- 04 Handles te reo, bilingual forms, and old NZ templates
Built on: Claude Vision AWS Textract Mistral OCR Vercel
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 document processing 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 Kwun Tong 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 document processing 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 |
What's different about doing this work in Kwun Tong.
- Kwun Tong has rebuilt itself from an industrial district into Hong Kong's startup and creative hub - AI here supports a business scene that's already used to reinventing fast.
- Former factory blocks have become one of the densest concentrations of startups, design studios and creative agencies in the city. Businesses here want AI that's genuinely modern, not a legacy tool with a new coat of paint.
We work with teams across Kwun Tong: Kowloon Bay · Ngau Tau Kok · Lam Tin · Cha Kwo Ling.
Talk to us about this →
How we build AI document processing for a Kwun Tong team.
We scope narrow, ship a working pilot, then harden it into production. The first slice is the highest-leverage workflow for your Kwun Tong business, so value lands before the build is finished. AI for paperwork.
Talk to usHow the work runs
- Find the one workflowWe look for the job costing Kwun Tong 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 Kwun Tong teams
We'd call the engagement a success when Kwun Tong teams are using the system without thinking about us. Cuts data-entry labour by 80% on invoices, POs, and timesheets.
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
When does AI document processing actually pay back?
Inside the first quarter, in our experience. We pick the first slice specifically because it's the highest-leverage workflow for a Kwun Tong - so the savings start landing before the rest of the build is finished.
Do you do hourly billing or fixed price?
Fixed price for the pilot, every time. After that it's your call - fixed price per milestone or a small monthly retainer for ongoing iteration. We don't run open-ended T&M because it disincentivises us from finishing.
Anyone else in this space using AI document processing?
Plenty. Cuts data-entry labour by 80% on invoices, POs, and timesheets. The interesting question is rarely "does it work" - it's "is your team ready to use the output." That's what we'd scope on the call.
Will this run on our own infrastructure?
Yes, where it makes sense. AI document processing can sit entirely in your cloud account, with model calls routed through endpoints you control. We default to Claude Vision, AWS Textract, Mistral OCR, Vercel but the architecture supports your existing platform choices.
The honest version of a sales call.
No deck. No discovery doc. Just whether this is worth building and what it would cost.
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.