AI efficiency audit in Wellington.
AI efficiency audit designed around the way a Wellington team actually runs.
What this is
Find AI wins fast
A two-week audit that maps your team's actual time spend, finds the 5 highest-leverage AI plays, and ships the first one. No vapourware, no 80-slide decks – just one working thing.
Average pilot saves 8 hours/week within 30 days of launch.
How it helps your Wellington team
What you actually get.
- Time-and-motion review of your top 5 workflows
- Ranked AI opportunity list – ROI, effort, risk
- One pilot shipped in week two, not a six-month roadmap
- Fixed price, fixed scope, kept honest
Wellington 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 efficiency audit template would catch.
Average pilot saves 8 hours/week within 30 days of launch. For Wellington teams, that almost always shows up as fewer interruptions and a calmer week, not a dashboard chart.
What Wellington teams tell us when they get on a call.
From central-government contractors to Kilbirnie tradies, Wellington teams want AI that respects security, privacy, and a healthy scepticism. We build accordingly.
We work with teams in
What we build
AI efficiency audit, tailored to Wellington businesses.
- 01 Time-and-motion review of your top 5 workflows
- 02 Ranked AI opportunity list – ROI, effort, risk
- 03 One pilot shipped in week two, not a six-month roadmap
- 04 Fixed price, fixed scope, kept honest
Common questions
Before you book the call.
What's the realistic timeline for AI efficiency audit with a Wellington? +
Most Wellington 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 efficiency audit worth it for a smaller Wellington? +
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.
Anyone else in this space using AI efficiency audit? +
Plenty. Average pilot saves 8 hours/week within 30 days of launch. 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.
What happens if we want to swap a vendor out later? +
AI efficiency audit 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, Notion, Loom, Linear, Vercel are our defaults, but the build is intentionally portable.
Twenty minutes, your call.
You describe what's broken. We'll tell you what we'd actually do about it.
Back to the form ↑