AI by role · New Zealand & Australia

AI for physicists who want fewer tabs open, not more.

Most physicists we talk to aren't short of software – they're short of an hour back in the day. That's the lens we put on AI for this role: not a tech showcase, but a careful look at the one workflow where physicists are paying for the same problem to be solved twice.

By the numbers

0.02% of all Claude.ai conversations map to this kind of work (Anthropic Economic Index, March 2026). For context, Australia's overall AI usage sits at 4.11× its expected level and Canada at 4.37× (with Singapore leading at 5.53×) — adoption is already well ahead of the curve, so the edge goes to whoever turns it into a concrete workflow first.

Physicists sits within Science & Research, one of the sectors we build production AI for.

Where AI helps

What changes for physicists week to week.

  • Summarise literature with citations.
  • Clean and explore datasets.
  • Draft methods and reports.
  • Answer questions over your documents.
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How we build AI for physicists.

We scope narrow, ship a working pilot, then harden it into production. The first slice is the highest-leverage workflow for your team, so value lands before the build is finished. The durable wins augment a person rather than replace them — a human approves anything that matters.

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The outcome for Physicists

We'd call the engagement a success when Physicists are using the system without thinking about us. 0.02% of all Claude.ai conversations map to this kind of work (Anthropic Economic Index, March 2026)

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.

Questions

FAQ

How fast could we have AI in production?

Eight to ten weeks for most Physicists. Faster if your data is in good shape and slower if we're untangling a legacy integration first. We'll give you a realistic number on the scoping call rather than the optimistic one.

What's the smallest engagement you'd take on?

A two-week paid discovery for Physicists that aren't sure whether the build is worth doing at all. You get a one-page write-up of what we'd build, what we'd skip, and what it would cost. About 30% of those discoveries end with us recommending you don't proceed.

Do you have proof this works for Physicists?

Direct case study: 0.02% of all Claude.ai conversations map to this kind of work (Anthropic Economic Index, March 2026) Happy to walk you through full numbers on a call.

What if our physicists team doesn't have any data ready?

Most don't. Getting the data into shape – ingestion, cleaning, the lightweight contracts you need before any model is useful – is part of the engagement. For AI specifically, we typically run that work on Summarise literature with citations, Clean and explore datasets, Draft methods and reports, Answer questions over your documents and assume messy starting conditions from day one.

Twenty minutes, your call.

You describe what's broken. We'll tell you what we'd actually do about it.

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Tell us what you're trying to do and we'll reply with how we'd build it — no obligation.