Kiwi Dynamics

Accounting firms · Applied AI

The version of semantic search (RAG) that accounting firms still use a year after launch.

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When a accounting firm asks us about semantic search (RAG), the first question we put back is the same one every time: which part of your week, if it disappeared, would change how you feel on a Friday? We start the build from that answer.

What semantic search (RAG) actually does

Search that understands intent, not just keywords. Your team types what they mean – and gets the right document, ticket, or product from across every system, with citations.

  • 01 Indexes Drive, SharePoint, Notion, Slack, your CRM
  • 02 Returns answers with source links – no hallucinations
  • 03 Permissioned so staff only see what they should
  • 04 Re-indexes nightly so results stay fresh

Built on: Pinecone Claude Postgres pgvector Vercel AI SDK

Why accounting firms are different

Accounting firms run their businesses unlike anyone else.

  • 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 semantic search (RAG) for accounting firms.

We scope narrow, ship a working pilot, then harden it into production. The first slice is the highest-leverage workflow for a accounting firm business, so value lands before the build is finished. AI search over your data.

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The outcome for accounting firms

If we build the right slice first, accounting firms feel the difference inside the first month. Average search time drops from 6 minutes to 12 seconds.

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.

Questions

FAQ

When does semantic search (RAG) 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 accounting firm – so the savings start landing before the rest of the build is finished.

How do you price semantic search (RAG) engagements?

Fixed-scope pilots first, then either project pricing or a small monthly retainer for the ongoing work. No long lock-ins, no 18-month black-box deals. Most accounting firms are surprised how small the first cheque is.

Anyone else in this space using semantic search (RAG)?

Plenty. Average search time drops from 6 minutes to 12 seconds. 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.

Will this run on our own infrastructure?

Yes, where it makes sense. Semantic search (RAG) can sit entirely in your cloud account, with model calls routed through endpoints you control. We default to Pinecone, Claude, Postgres pgvector, Vercel AI SDK but the architecture supports your existing platform choices.

The honest version of a sales call.

No deck. No discovery doc. Just whether this is worth building and what it would cost.

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Tell us what you're trying to do and we'll reply with how we'd build it — no obligation.