AI personalised CX - wired into a San Francisco workflow, not bolted on the side.

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

San Francisco 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 personalisation template would catch.

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

The pattern across San Francisco engagements we've shipped.

  • San Francisco is where the AI industry itself is headquartered - any AI pitched here is judged against the frontier labs a few blocks away, not against a competitor's landing page.
  • The highest concentration of AI research labs and startups anywhere in the world, sitting alongside legacy finance and professional services firms adopting AI for the first time. San Francisco is the least forgiving market for a weak AI product, and the best one for a genuinely strong one.

We work with teams across San Francisco: Financial District · SoMa · Mission District · Marina · Nob Hill · Hayes Valley.

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How we build AI personalisation for a San Francisco team.

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

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How the work runs

The outcome for San Francisco teams

The shape of the result for San Francisco teams: Conversion lift of 18-32% over generic site experiences. 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

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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.

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*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 San Francisco?

Most San Francisco 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".

Is AI personalisation worth it for a smaller San Francisco?

Often, yes - and counterintuitively the ROI is sometimes faster than for the big end of town because there's less integration overhead. We'll tell you honestly on the scoping call if it isn't.

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. Conversion lift of 18-32% over generic site experiences.

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.