AI efficiency audit designed around the way a San Francisco team actually runs.

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 :)

San Francisco 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 efficiency audit template would catch.

What AI efficiency audit actually does

A two-week audit that maps your team's actual time spend, finds the 5 highest-leverage AI plays, and ships the first one. No vapourware, no 80-slide decks - just one working thing.

  • 01 Time-and-motion review of your top 5 workflows
  • 02 Ranked AI opportunity list - ROI, effort, risk
  • 03 One pilot shipped in week two, not a six-month roadmap
  • 04 Fixed price, fixed scope, kept honest

Built on: Claude Notion Loom Linear Vercel

What you actually get

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

How AI efficiency audit 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 San Francisco.

  • 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 efficiency audit 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. Find AI wins fast.

Talk to us

How the work runs

The outcome for San Francisco teams

Average pilot saves 8 hours/week within 30 days of launch. For San Francisco 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

Start a conversation

*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 efficiency audit with a San Francisco?

Most San Francisco 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 efficiency audit worth it for a smaller San Francisco?

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.

Do you have proof this works for San Francisco businesses?

Direct case study: Average pilot saves 8 hours/week within 30 days of launch. Happy to walk you through full numbers on a call.

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

AI efficiency audit 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, Notion, Loom, Linear, Vercel 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.