AI agents that lives in your stack, not on a vendor's roadmap. Shipped from New York.

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

The reason we take on work in New York is that the businesses here tend to be sharper about what they want than the brief lets on. AI agents for a New York team almost always ends up looking different to AI agents for a downtown Auckland one.

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

What we keep seeing in New York.

  • New York runs on finance, law, media and a professional services machine that bills by the hour - AI here earns its place by giving that time back, not by being impressive in a demo.
  • Wall Street firms, Big Law, and a media and advertising industry that never fully stops, all sitting on top of the highest labour costs in the country. New York teams want AI that survives contact with a real client deadline.

We work with teams across New York: Manhattan · Brooklyn · Queens · Midtown · Financial District · Long Island City.

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How we build AI agents for a New York team.

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

The shape of the result for New York 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 New York?

Most New York 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 New York?

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.

Anyone else in this space using AI agents?

Plenty. Replaces 15+ hours of weekly back-office work per agent deployed. The interesting question is rarely "does it work" - it's "is your team ready to use the output." That's what we'd scope on the 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.

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.