Every materials scientists team we've worked with has a different definition of "broken". AI only earns its keep when it solves the specific definition you'd give it on a bad day – which is why our first call is mostly listening.
AI by role · New Zealand & Australia
Built for the parts of the materials scientists job that eat a Tuesday.
By the numbers
0.11% 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.
Materials Scientists sits within Science & Research, one of the sectors we build production AI for.
Without Kiwi Dynamics
With Kiwi Dynamics
Where AI helps
What changes for materials scientists week to week.
- Summarise literature with citations.
- Clean and explore datasets.
- Draft methods and reports.
- Answer questions over your documents.
How we build AI for materials scientists.
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.
Talk to usThe outcome for Materials Scientists
If we build the right slice first, Materials Scientists feel the difference inside the first month. 0.11% 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
*Every engagement is scoped and quoted up front. Results vary by workflow and business.
Questions
FAQ
When does AI actually pay back?
Inside the first quarter, in our experience. We pick the first slice specifically because it's the highest-leverage workflow for a materials scientists team – so the savings start landing before the rest of the build is finished.
How do you price AI engagements?
Fixed-scope pilots first, then either project pricing or a small monthly retainer for the ongoing work. No long lock-ins, no 18-month black-box deals. Most Materials Scientists are surprised how small the first cheque is.
Anyone else in this space using AI?
Plenty. 0.11% of all Claude.ai conversations map to this kind of work (Anthropic Economic Index, March 2026) The interesting question is rarely "does it work" – it's "is your team ready to use the output." That's what we'd scope on the call.
Will this run on our own infrastructure?
Yes, where it makes sense. AI can sit entirely in your cloud account, with model calls routed through endpoints you control. We default to Summarise literature with citations, Clean and explore datasets, Draft methods and reports, Answer questions over your documents but the architecture supports your existing platform choices.
Worth a conversation?
Even if you don't end up working with us, you'll leave the call knowing what's worth building.
Get in touch
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.