Kiwi Dynamics

Bay of Plenty · Applied AI

Semantic search (RAG) that lives in your stack, not on a vendor's roadmap. Shipped from Bay of Plenty.

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Whakatāne 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 semantic search (RAG) template would catch.

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

Bay of Plenty

The pattern across Whakatāne engagements we've shipped.

  • Eastern Bay of Plenty runs on horticulture, aquaculture, and Māori-led enterprise – AI here works when it respects relationships first.
  • Kiwifruit, aquaculture, marine tourism, and a strong iwi economy. AI tools that work offline and bilingually find their home here.

We work with teams across Whakatāne: Whakatāne · Ōhope · Kawerau · Edgecumbe · Murupara · Ōpōtiki.

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How we build semantic search (RAG) for a Whakatāne team.

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

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The outcome for Whakatāne teams

If we build the right slice first, Whakatāne teams 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

How fast could we have semantic search (RAG) in production?

Eight to ten weeks for most Whakatāne 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 does semantic search (RAG) cost for a Whakatāne?

Pilots start from a fixed scope priced to land a measurable result inside 6 weeks. Pricing depends on data volume, integration complexity, and whether you need us on managed services afterwards. We'll quote precisely after a 30-minute scoping call.

Do you have proof this works for Whakatāne businesses?

Direct case study: Average search time drops from 6 minutes to 12 seconds. Happy to walk you through full numbers on a call.

What if our Whakatāne 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 semantic search (RAG) specifically, we typically run that work on Pinecone, Claude, Postgres pgvector, Vercel AI SDK and assume messy starting conditions from day one.

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We'll map your real workflow before quoting anything.

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