Accounting firms-grade AI call summaries, shipped by people who've done it before.

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

Most accounting firms we talk to aren't short of dashboards or tools - they're short of an hour back in the week. That's the lens we put on AI call summaries: not a tech showcase, but a careful look at the one or two workflows where an accounting firm is paying for the same problem to be solved twice.

What AI call summaries actually does

Every customer call recorded, transcribed, summarised, and coached. Managers spot what's working, reps see what to fix, and customers get follow-ups that actually reference what they said.

  • 01 Auto-summary into your CRM after every call
  • 02 Coaching scorecards for sales and support reps
  • 03 Detects compliance phrases (or missing ones)
  • 04 Searchable archive - find the call that mentioned X

Built on: Twilio AssemblyAI Claude Vercel

What you actually get

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

How AI call summaries 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

The two or three things that decide whether this works for accounting firms.

  • Accounting firms carry seasonal peaks where document chasing and data entry crowd out the advisory work that actually pays.
  • Client document requests, reconciliations, and deadline reminders are the repetitive load behind every busy season.
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How we build AI call summaries for accounting firms.

We scope narrow, ship a working pilot, then harden it into production. The first slice is the highest-leverage workflow for an accounting firm business, so value lands before the build is finished. AI call notes + coaching.

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How the work runs

The outcome for accounting firms

What changes for accounting firms 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. Sales coaching scales to every rep without doubling manager time.

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 call summaries with an accounting firm?

Most accounting firms 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 call summaries worth it for a smaller accounting firm?

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.

What's the realistic outcome for accounting firms?

Sales coaching scales to every rep without doubling manager time. We don't promise tenfold lifts because we don't see them outside of marketing decks.

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

AI call summaries 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. Twilio, AssemblyAI, Claude, Vercel are our defaults, but the build is intentionally portable.

One short call.

Tell us what you're trying to fix. We'll come back inside a working day.

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.