Roofing companies · Applied AI

Ask your data in English, built around how a roofing company actually works.

AI data analytics is overhyped at the macro level and underused at the workflow level. For a NZ roofing company, that gap is where the actual ROI lives – and where most of our work happens.

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

Sector reality

Roofing companies need software built around their week, not against it.

  • Roofers quote off photos, chase weather windows, and juggle insurance jobs that all move at different speeds.
  • Fast, accurate quoting from a photo is the single biggest lever for a roofing business's close rate.
Talk to us about this →

How we build AI data analytics for roofing companies.

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

Talk to us

The outcome for roofing companies

What changes for roofing companies 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. Owners check the business in 2 minutes instead of 2 hours.

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

When does AI data analytics 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 roofing company – so the savings start landing before the rest of the build is finished.

Do you do hourly billing or fixed price?

Fixed price for the pilot, every time. After that it's your call – fixed price per milestone or a small monthly retainer for ongoing iteration. We don't run open-ended T&M because it disincentivises us from finishing.

Has this actually shipped for a real roofing company?

Yes. Owners check the business in 2 minutes instead of 2 hours. We'll share comparable engagements on the call.

Will this run on our own infrastructure?

Yes, where it makes sense. AI data analytics can sit entirely in your cloud account, with model calls routed through endpoints you control. We default to DuckDB, Claude, Metabase, BigQuery, Vercel AI SDK 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.