AI personalisation that lives in your stack, not on a vendor's roadmap. Shipped from Florida.

Our goal is to give Miami businesses a three-day weekend, so people can spend more time with their families and the people they love :)

The reason we take on work in Miami is that the businesses here tend to be sharper about what they want than the brief lets on. AI personalisation for a Miami team almost always ends up looking different to AI personalisation for a downtown Auckland one.

What AI personalisation actually does

Every customer sees the right product, message, and offer - based on what they've bought, browsed, and asked. Built on first-party data, no creepy tracking required.

  • 01 Per-customer recommendations across web and email
  • 02 Dynamic landing pages tailored to traffic source
  • 03 Lifecycle messaging triggered by real behaviour
  • 04 GDPR + NZ Privacy Act compliant by default

Built on: Claude Vercel Edge Postgres Klaviyo

What you actually get

Every engagement is scoped and quoted up front. This is what is in the box.

How AI personalisation compares

The two things most businesses do instead, and where each one runs out.

 Hiring for itAn off-the-shelf toolKiwi Dynamics
Fit to how you workFits perfectly, costs a salaryYou bend your process to suit the toolBuilt around the workflow you already run
Time to something usefulImmediate, and permanentQuick to switch on, slow to make fitA working slice in weeks, then hardened
Who owns the dataYou doThe vendor, on the vendor's termsYou do, in your own accounts
When it breaksThat person sorts it, if they are inA support queue and a ticket numberThe people who built it
What it costsA salary, every year, foreverPer seat, forever, used or notScoped and quoted up front

Our field notes from Miami builds.

  • Miami runs on trade, tourism and a wave of finance and tech relocations from the Northeast - AI here means serving a bilingual, fast-moving market that operates around the clock.
  • A major gateway for trade with Latin America, a tourism economy that runs year-round, and a newer wave of finance and tech companies relocating in. Miami businesses want AI that works as comfortably in Spanish as English.

We work with teams across Miami: Downtown Miami · Brickell · Coral Gables · Wynwood · Miami Beach · Doral.

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How we build AI personalisation for a Miami team.

We scope narrow, ship a working pilot, then harden it into production. The first slice is the highest-leverage workflow for your Miami business, so value lands before the build is finished. AI personalised CX.

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How the work runs

The outcome for Miami teams

Conversion lift of 18-32% over generic site experiences. For Miami teams, that almost always shows up as fewer interruptions and a calmer week, not a dashboard chart.

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

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*Every engagement is scoped and quoted up front. Results vary by workflow and business.

How much is not automating costing you?

Nine hours a week of admin is 468 hours a year. With Kiwi Dynamics, that drops to about 52.

Try the calculator

*Based on 9 hours a week of admin at Kiwi Dynamics' typical 80% automation rate. Your number may vary, the calculator uses your own.

FAQ

What's the realistic timeline for AI personalisation with a Miami?

Most Miami businesses have their first usable slice in week 5 or 6. We'd rather ship narrow and real than broad and aspirational - your team gets to use the thing well before the engagement is "done".

What does AI personalisation cost for a Miami?

Pilots start from a fixed scope priced to land a measurable result inside 6 weeks. Pricing depends on data volume, integration complexity, and whether you need us on managed services afterwards. We'll quote precisely after a 30-minute scoping call.

Do you have proof this works for Miami businesses?

Direct case study: Conversion lift of 18-32% over generic site experiences. Happy to walk you through full numbers on a call.

What happens if we want to swap a vendor out later?

AI personalisation is built behind a small adapter layer specifically so swapping a model provider or a data source is a one-day job, not a re-architecture. Claude, Vercel Edge, Postgres, Klaviyo are our defaults, but the build is intentionally portable.

Sketch this with us.

We'll map your real workflow before quoting anything.

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.