We've worked with enough operators in San Francisco to know that the brief that arrives in our inbox is rarely the brief that ends up shipped. The first thing we do on any AI agents project is sit with your team for a day before we propose anything.
AI agents that do work, built for businesses operating in San Francisco.
Our goal is to give San Francisco businesses a three-day weekend, so people can spend more time with their families and the people they love :)
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
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 agents 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 San Francisco 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 agents 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 |
Where San Francisco operators actually lose hours.
- San Francisco is where the AI industry itself is headquartered - any AI pitched here is judged against the frontier labs a few blocks away, not against a competitor's landing page.
- The highest concentration of AI research labs and startups anywhere in the world, sitting alongside legacy finance and professional services firms adopting AI for the first time. San Francisco is the least forgiving market for a weak AI product, and the best one for a genuinely strong one.
We work with teams across San Francisco: Financial District · SoMa · Mission District · Marina · Nob Hill · Hayes Valley.
Talk to us about this →
How we build AI agents for a San Francisco team.
We scope narrow, ship a working pilot, then harden it into production. The first slice is the highest-leverage workflow for your San Francisco business, so value lands before the build is finished. AI agents that do work.
Talk to usHow the work runs
- Find the one workflowWe look for the job costing San Francisco 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 San Francisco teams
If we build the right slice first, San Francisco teams feel the difference inside the first month. 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
*Every engagement is scoped and quoted up front. Results vary by workflow and business.
FAQ
When does AI agents actually pay back?
Inside the first quarter, in our experience. We pick the first slice specifically because it's the highest-leverage workflow for a San Francisco - so the savings start landing before the rest of the build is finished.
Do you do hourly billing or fixed price?
Fixed price for the pilot, every time. After that it's your call - fixed price per milestone or a small monthly retainer for ongoing iteration. We don't run open-ended T&M because it disincentivises us from finishing.
Do you have proof this works for San Francisco 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.
Will this run on our own infrastructure?
Yes, where it makes sense. AI agents can sit entirely in your cloud account, with model calls routed through endpoints you control. We default to Claude Agent SDK, OpenAI Agents, LangGraph, n8n, MCP but the architecture supports your existing platform choices.
Skip the pitch.
Tell us the workflow and we'll come back with what we'd build first.
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.