AI call summaries that lives in your stack, not on a vendor's roadmap. Shipped from Nelson-Tasman.

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

Nelson 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 call summaries template would catch.

What AI call summaries actually does

Every customer call recorded, transcribed, summarised, and coached. Managers spot what's working, reps see what to fix, and customers get follow-ups that actually reference what they said.

  • 01 Auto-summary into your CRM after every call
  • 02 Coaching scorecards for sales and support reps
  • 03 Detects compliance phrases (or missing ones)
  • 04 Searchable archive - find the call that mentioned X

Built on: Twilio AssemblyAI Claude Vercel

What you actually get

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

How AI call summaries 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 Nelson builds.

  • Nelson is creative, outdoorsy, and full of clever small businesses - AI here is about giving owner-operators their evenings back.
  • Aquaculture, hops, tourism, and a deep creative sector. Nelson teams want tools that fit a smaller crew without enterprise overhead.

We work with teams across Nelson: CBD · Stoke · Tahunanui · Richmond · Motueka · Brightwater.

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How we build AI call summaries for a Nelson team.

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

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How the work runs

The outcome for Nelson teams

Sales coaching scales to every rep without doubling manager time. For Nelson 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.

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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 call summaries with a Nelson?

Most Nelson 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 call summaries cost for a Nelson?

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.

What's the realistic outcome for Nelson businesses?

Sales coaching scales to every rep without doubling manager time. We don't promise tenfold lifts because we don't see them outside of marketing decks.

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

AI call summaries 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. Twilio, AssemblyAI, Claude, Vercel 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.