Find AI wins fast - wired into a Boston workflow, not bolted on the side.

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

Boston businesses don't need another generic AI pitch. AI efficiency audit 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 Massachusetts.

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 Boston teams tell us when they get on a call.

  • Boston runs on biotech, higher education and finance, with more PhDs per capita than almost anywhere in the country - AI here has to earn trust from a genuinely technical audience.
  • A world-leading biotech and pharma cluster, a huge concentration of universities and hospitals, and a mature financial services industry. Boston businesses expect AI claims to be backed by something more rigorous than a demo.

We work with teams across Boston: Back Bay · Cambridge · Seaport · Somerville · South End · Kendall Square.

Talk to us about this →

How we build AI efficiency audit for a Boston team.

We scope narrow, ship a working pilot, then harden it into production. The first slice is the highest-leverage workflow for your Boston business, so value lands before the build is finished. Find AI wins fast.

Talk to us

How the work runs

The outcome for Boston teams

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

How fast could we have AI efficiency audit in production?

Eight to ten weeks for most Boston businesses. Faster if your data is in good shape and slower if we're untangling a legacy integration first. We'll give you a realistic number on the scoping call rather than the optimistic one.

What's the smallest engagement you'd take on?

A two-week paid discovery for Boston businesses that aren't sure whether the build is worth doing at all. You get a one-page write-up of what we'd build, what we'd skip, and what it would cost. About 30% of those discoveries end with us recommending you don't proceed.

Anyone else in this space using AI efficiency audit?

Plenty. Average pilot saves 8 hours/week within 30 days of launch. 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 if our Boston doesn't have any data ready?

Most don't. Getting the data into shape - ingestion, cleaning, the lightweight contracts you need before any model is useful - is part of the engagement. For AI efficiency audit specifically, we typically run that work on Claude, Notion, Loom, Linear, Vercel and assume messy starting conditions from day one.

One reply, one direction.

We don't run sequences or follow-up automation. One useful answer, one decision on your side.

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.