We've worked with enough operators in Changi 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 efficiency audit project is sit with your team for a day before we propose anything.
For Changi operators who want a working pilot in weeks, not a year-long programme.
Our goal is to give Changi businesses a three-day weekend, so people can spend more time with their families and the people they love :)
What AI efficiency audit actually does
A two-week audit that maps your team's actual time spend, finds the 5 highest-leverage AI plays, and ships the first one. No vapourware, no 80-slide decks - just one working thing.
- 01 Time-and-motion review of your top 5 workflows
- 02 Ranked AI opportunity list - ROI, effort, risk
- 03 One pilot shipped in week two, not a six-month roadmap
- 04 Fixed price, fixed scope, kept honest
Built on: Claude Notion Loom Linear 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 efficiency audit 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 Changi 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 efficiency audit 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 |
The Changi context, plainly.
- Changi runs on aviation, logistics and air cargo as one of the world's busiest air hubs - AI here means keeping freight, scheduling and compliance moving at airport speed.
- Changi Airport and its surrounding air-cargo and logistics ecosystem move an enormous volume of freight and passengers on tight schedules. Businesses here want AI that handles logistics coordination and compliance documentation without becoming the bottleneck.
We work with teams across Changi: Changi Airport · Changi Business Park · Loyang · Pasir Ris · Tampines.
Talk to us about this →
How we build AI efficiency audit for a Changi team.
We scope narrow, ship a working pilot, then harden it into production. The first slice is the highest-leverage workflow for your Changi business, so value lands before the build is finished. Find AI wins fast.
Talk to usHow the work runs
- Find the one workflowWe look for the job costing Changi 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 Changi teams
The shape of the result for Changi teams: Average pilot saves 8 hours/week within 30 days of launch. Built on Claude, hardened with the rest of the stack as it scales.
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
What's a typical engagement length for Changi businesses?
Six to twelve weeks for the build, then a short managed-services month while the system goes from "shipped" to "owned by your team". After that you keep us on retainer if you want, or take it from there yourself.
Are there hidden costs we should plan for?
Three to know about: model/API spend (which we set up under your own account, not ours, so you see and control it), any new SaaS subscriptions we recommend, and your team's time during rollout. We surface all three in the quote so there are no surprises.
Has this actually shipped for a real Changi?
Yes. Average pilot saves 8 hours/week within 30 days of launch. We'll share comparable engagements on the call.
Can you work with our existing systems?
Yes. The default AI efficiency audit stack we reach for is Claude, Notion, Loom, Linear, Vercel, but we'll bend it around whatever you already run - Xero, HubSpot, Shopify, Cin7, your own in-house apps. The discovery week maps every data source before any build starts.
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.