The version of AI agents that works for a Wānaka business is rarely the version a national vendor would sell you. We build the one that fits how your team actually operates – usually with fewer parts than the off-the-shelf pitch.
Otago · Applied AI
Built and supported here – the way a Wānaka business would actually use it.
What AI agents actually does
Autonomous AI agents that don't just answer – they get things done. They check inventory, draft proposals, file paperwork, and chase quotes while your team focuses on the human work.
- 01 Goal-driven agents that complete multi-step tasks
- 02 Connect to your tools – Xero, HubSpot, Gmail, Slack, your CRM
- 03 Human-in-the-loop checkpoints for anything risky
- 04 Full audit log of every action the agent takes
Built on: Claude Agent SDK OpenAI Agents LangGraph n8n MCP
Otago
What's different about doing this work in Wānaka.
- Wānaka has the boom-and-shoulder rhythm of a lifestyle town – AI here helps small teams handle big seasonal swings without burning out.
- Tourism, hospitality, lifestyle property, and trades feeding constant builds. AI shines when it lets a small operator look like a big one.
We work with teams across Wānaka: Wānaka township · Albert Town · Hāwea · Cardrona · Lake Hāwea.
Talk to us about this →How we build AI agents for a Wānaka team.
We scope narrow, ship a working pilot, then harden it into production. The first slice is the highest-leverage workflow for your Wānaka business, so value lands before the build is finished. AI agents that do work.
Talk to usThe outcome for Wānaka teams
What changes for Wānaka teams after this lands: the work that used to need a person stays done, the work that needs a person gets done with their attention undivided. Replaces 15+ hours of weekly back-office work per agent deployed.
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 agents 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 Wānaka – so the savings start landing before the rest of the build is finished.
How do you price AI agents 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 Wānaka businesses are surprised how small the first cheque is.
Anyone else in this space using AI agents?
Plenty. Replaces 15+ hours of weekly back-office work per agent deployed. 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 agents can sit entirely in your cloud account, with model calls routed through endpoints you control. We default to Claude Agent SDK, OpenAI Agents, LangGraph, n8n, MCP but the architecture supports your existing platform choices.
The honest version of a sales call.
No deck. No discovery doc. Just whether this is worth building and what it would cost.
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.