Hair salons · Applied AI

Hair salons-grade AI data analytics, shipped by people who've done it before.

Hair salons are some of the most efficient operators in New Zealand – which means the easy wins from AI data analytics are usually already taken. The brief we accept is the one focused on the workflow you've tried to fix twice and given up on.

What AI data analytics actually does

Stop digging through dashboards. Ask plain-English questions of your sales, jobs, and customer data – get charts, summaries, and the why behind the numbers in seconds.

  • 01 Natural-language queries over your Xero, Shopify, CRM data
  • 02 Weekly auto-summaries delivered to inbox or Slack
  • 03 Anomaly detection – flags weird weeks before you notice
  • 04 Forecasts that explain themselves, not black boxes

Built on: DuckDB Claude Metabase BigQuery Vercel AI SDK

Lay of the land

The two or three things that decide whether this works for hair salons.

  • Salons run on a fully booked chair, and every gap in the calendar is revenue that doesn't come back.
  • Rebooking, no-show follow-ups, and client reminders are what keep a salon's calendar full without constant manual chasing.
Talk to us about this →

How we build AI data analytics for hair salons.

We scope narrow, ship a working pilot, then harden it into production. The first slice is the highest-leverage workflow for a hair salon business, so value lands before the build is finished. Ask your data in English.

Talk to us

The outcome for hair salons

The shape of the result for hair salons: Owners check the business in 2 minutes instead of 2 hours. Built on DuckDB, hardened with the rest of the stack as it scales.

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

Start a conversation

*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.

Try the calculator

*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 quickly can we see something running?

Week three for a clickable internal demo against real data. Week six for a slice your team can actually use. We hold ourselves to those numbers because they're what stops a project drifting into "endless discovery".

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

A two-week paid discovery for hair salons 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 hair salons?

Direct case study: Owners check the business in 2 minutes instead of 2 hours. Happy to walk you through full numbers on a call.

What tools do you build AI data analytics on?

For AI data analytics we usually reach for DuckDB, Claude, Metabase, BigQuery, Vercel AI SDK. We're tool-agnostic at heart – we pick what your hair salon team can actually run after we hand the build over, not what looks good on a vendor sticker.

Twenty minutes, your call.

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

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.