AI agents 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 :)

Seattle businesses don't need another generic AI pitch. AI agents 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 agents actually does

Autonomous AI agents that don't just answer - they get things done. They check inventory, draft proposals, file paperwork, and chase quotes while your team focuses on the human work.

  • 01 Goal-driven agents that complete multi-step tasks
  • 02 Connect to your tools - Xero, HubSpot, Gmail, Slack, your CRM
  • 03 Human-in-the-loop checkpoints for anything risky
  • 04 Full audit log of every action the agent takes

Built on: Claude Agent SDK OpenAI Agents LangGraph n8n MCP

What you actually get

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

How AI agents 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

Our field notes from Seattle builds.

  • 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 agents 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 agents that do work.

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How the work runs

The outcome for Seattle teams

The shape of the result for Seattle teams: Replaces 15+ hours of weekly back-office work per agent deployed. Built on Claude Agent SDK, 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

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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.

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*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 agents with a Seattle?

Most Seattle 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 agents worth it for a smaller Seattle?

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.

Can you walk us through a comparable build?

Yes - on the first call we'll pick the closest engagement we've shipped to what you're describing and walk through the outcome, the headcount and the time it took. Replaces 15+ hours of weekly back-office work per agent deployed.

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

AI agents 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 Agent SDK, OpenAI Agents, LangGraph, n8n, MCP are our defaults, but the build is intentionally portable.

One short call.

Tell us what you're trying to fix. We'll come back inside a working day.

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.