The reason we take on work in Seattle is that the businesses here tend to be sharper about what they want than the brief lets on. AI staff training for a Seattle team almost always ends up looking different to AI staff training for a downtown Auckland one.
AI staff training designed around the way a Seattle team actually runs.
Our goal is to give Seattle businesses a three-day weekend, so people can spend more time with their families and the people they love :)
What AI staff training actually does
Turn your senior team's brain into interactive training. AI-generated lessons, practice scenarios, and on-the-job coaching that scales without burning out your best people.
- 01 Auto-generates training modules from your SOPs
- 02 Voice-based roleplay scenarios for sales and service teams
- 03 Tracks competency and flags refresher needs
- 04 Works offline on site or in the truck
Built on: Claude ElevenLabs Vercel AI SDK Mux Postgres
Without Kiwi Dynamics
With Kiwi Dynamics
What you actually get
Every engagement is scoped and quoted up front. This is what is in the box.
- A working pilot, in productionNot a prototype on someone's laptop. The first slice of AI staff training runs against real work within weeks.
- Your data stays yoursIt runs on your accounts and your tools. If we part ways you keep the system and everything in it.
- The workflow mapped before codeWe write down what good looks like for Seattle businesses first, so nobody is guessing at handover.
- Support after it landsThe people who built it stay reachable when the business changes shape around it.
How AI staff training compares
The two things most businesses do instead, and where each one runs out.
| Hiring for it | An off-the-shelf tool | Kiwi Dynamics | |
|---|---|---|---|
| Fit to how you work | Fits perfectly, costs a salary | You bend your process to suit the tool | Built around the workflow you already run |
| Time to something useful | Immediate, and permanent | Quick to switch on, slow to make fit | A working slice in weeks, then hardened |
| Who owns the data | You do | The vendor, on the vendor's terms | You do, in your own accounts |
| When it breaks | That person sorts it, if they are in | A support queue and a ticket number | The people who built it |
| What it costs | A salary, every year, forever | Per seat, forever, used or not | Scoped and quoted up front |
The pattern across Seattle engagements we've shipped.
- Seattle runs on cloud computing, aerospace and coffee, home to the companies whose infrastructure half the internet's AI runs on - AI here means holding up to serious technical scrutiny.
- Two of the world's largest cloud providers are headquartered here alongside a major aerospace manufacturing base. Seattle businesses, even small ones, tend to have someone on staff who can and will check your work.
We work with teams across Seattle: Downtown Seattle · Capitol Hill · Bellevue · Fremont · Ballard · Redmond.
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How we build AI staff training for a Seattle team.
We scope narrow, ship a working pilot, then harden it into production. The first slice is the highest-leverage workflow for your Seattle business, so value lands before the build is finished. AI training tools.
Talk to usHow the work runs
- Find the one workflowWe look for the job costing Seattle businesses the most hours or the most leads, and deliberately ignore the rest for now.
- Ship a working sliceA narrow version goes into production in weeks, against real work, so the value shows up before the build is finished.
- Prove it, then widenWe measure it against what the work cost before. If it does not pay for itself, we say so rather than scaling it.
- Harden and hand overLogging, fallbacks and a real handover, so it keeps running when we are not in the room.
The outcome for Seattle teams
New-hire ramp-up cut from 12 weeks to 5 - measurable competency, not just attendance. For Seattle teams, that almost always shows up as fewer interruptions and a calmer week, not a dashboard chart.
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.
FAQ
How fast could we have AI staff training in production?
Eight to ten weeks for most Seattle businesses. Faster if your data is in good shape and slower if we're untangling a legacy integration first. We'll give you a realistic number on the scoping call rather than the optimistic one.
What's the smallest engagement you'd take on?
A two-week paid discovery for Seattle businesses 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.
What's the realistic outcome for Seattle businesses?
New-hire ramp-up cut from 12 weeks to 5 - measurable competency, not just attendance. We don't promise tenfold lifts because we don't see them outside of marketing decks.
What if our Seattle doesn't have any data ready?
Most don't. Getting the data into shape - ingestion, cleaning, the lightweight contracts you need before any model is useful - is part of the engagement. For AI staff training specifically, we typically run that work on Claude, ElevenLabs, Vercel AI SDK, Mux, Postgres and assume messy starting conditions from day one.
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.