AI sales + stock forecasting - wired into a Spokane workflow, not bolted on the side.

Our goal is to give Spokane businesses a three-day weekend, so people can spend more time with their families and the people they love :)

Spokane businesses don't need another generic AI pitch. AI demand forecasting only earns its keep when it's built around the workflow you actually run on a wet Tuesday, and that's how we scope every engagement we take on in Washington.

What AI demand forecasting actually does

Forecasts that account for school holidays, NZ weather, tourist seasons, and your own promo calendar. Order the right stock, roster the right hours, plan the next quarter with actual numbers.

  • 01 Combines your sales history with weather, calendar, and event data
  • 02 Per-SKU and per-store forecasts, not whole-business averages
  • 03 Re-forecasts weekly as new data comes in
  • 04 Explains the why behind every number

Built on: Prophet DuckDB Claude BigQuery Vercel

What you actually get

Every engagement is scoped and quoted up front. This is what is in the box.

How AI demand forecasting compares

The two things most businesses do instead, and where each one runs out.

 Hiring for itAn off-the-shelf toolKiwi Dynamics
Fit to how you workFits perfectly, costs a salaryYou bend your process to suit the toolBuilt around the workflow you already run
Time to something usefulImmediate, and permanentQuick to switch on, slow to make fitA working slice in weeks, then hardened
Who owns the dataYou doThe vendor, on the vendor's termsYou do, in your own accounts
When it breaksThat person sorts it, if they are inA support queue and a ticket numberThe people who built it
What it costsA salary, every year, foreverPer seat, forever, used or notScoped and quoted up front

The pattern across Spokane engagements we've shipped.

  • Spokane is the commercial hub of the Inland Northwest, running on healthcare, logistics and agriculture far from the Seattle price tag - AI here means real capability at a regional cost.
  • A major regional healthcare network and a logistics and agricultural trade hub serving eastern Washington and Idaho. Spokane businesses want the same AI capability as the coast without paying coastal rates.

We work with teams across Spokane: Downtown Spokane · Browne's Addition · Spokane Valley · South Hill · Kendall Yards · Liberty Lake.

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How we build AI demand forecasting for a Spokane team.

We scope narrow, ship a working pilot, then harden it into production. The first slice is the highest-leverage workflow for your Spokane business, so value lands before the build is finished. AI sales + stock forecasting.

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How the work runs

The outcome for Spokane teams

We'd call the engagement a success when Spokane teams are using the system without thinking about us. Stockouts down 35%, overstock down 22% in the first season.

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

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*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.

FAQ

What's the realistic timeline for AI demand forecasting with a Spokane?

Most Spokane 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 demand forecasting worth it for a smaller Spokane?

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.

Do you have proof this works for Spokane businesses?

Direct case study: Stockouts down 35%, overstock down 22% in the first season. Happy to walk you through full numbers on a call.

What happens if we want to swap a vendor out later?

AI demand forecasting 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. Prophet, DuckDB, Claude, BigQuery, 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.

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.