AI agents designed around the way a Portland team actually runs.

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

Portland sits in a regional context that genuinely changes the build. Connectivity assumptions, the rhythm of the working week, the proximity of your team to your customers - none of those are details our default AI agents template would catch.

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 Portland builds.

  • Portland runs on a mix of tech, manufacturing and a famously independent small business scene - AI here has to respect a market that's skeptical of hype by default.
  • A semiconductor and tech manufacturing base (the 'Silicon Forest'), and a dense scene of independent retailers, restaurants and makers. Portland businesses want AI that's genuinely useful, not just the current trend.

We work with teams across Portland: Downtown Portland · Pearl District · Hawthorne · Beaverton · Hillsboro · Lloyd District.

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How we build AI agents for a Portland team.

We scope narrow, ship a working pilot, then harden it into production. The first slice is the highest-leverage workflow for your Portland 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 Portland teams

What changes for Portland teams 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. Replaces 15+ hours of weekly back-office work per agent deployed.

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 agents with a Portland?

Most Portland 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".

What does AI agents cost for a Portland?

Pilots start from a fixed scope priced to land a measurable result inside 6 weeks. Pricing depends on data volume, integration complexity, and whether you need us on managed services afterwards. We'll quote precisely after a 30-minute scoping call.

Do you have proof this works for Portland businesses?

Direct case study: Replaces 15+ hours of weekly back-office work per agent deployed. Happy to walk you through full numbers on a call.

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.

Sketch this with us.

We'll map your real workflow before quoting anything.

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.