Northland · Applied AI

AI knowledge base designed around the way a Kerikeri team actually runs.

Kerikeri 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 knowledge base template would catch.

What AI knowledge base actually does

Your team's tribal knowledge, finally searchable. Upload your SOPs, training videos, past emails, and Slack threads – your team asks questions and gets answers with citations.

  • 01 Ingests PDFs, Word docs, videos, Slack, Notion, Drive
  • 02 Answers with citations back to source documents
  • 03 Permission-aware – staff only see what they should
  • 04 Detects stale docs and prompts owners to update

Built on: Claude Pinecone Vercel AI SDK Postgres MCP

Northland

What we keep seeing in Kerikeri.

  • Kerikeri is horticulture, tourism, and a fast-growing lifestyle community – AI here is about connecting orchard, paddock, and storefront.
  • Kiwifruit, citrus, and a steady hospitality scene serving the Bay of Islands. AI tools that work in low-signal areas land best.

We work with teams across Kerikeri: Kerikeri central · Waipapa · Kaitāia · Russell · Paihia · Mangonui.

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How we build AI knowledge base for a Kerikeri team.

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

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The outcome for Kerikeri teams

The shape of the result for Kerikeri teams: New staff get to productive 3x faster – less senior-team interruption. Built on Claude, hardened with the rest of the stack as it scales.

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 AI knowledge base in production?

Eight to ten weeks for most Kerikeri 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 Kerikeri 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.

What's the realistic outcome for Kerikeri businesses?

New staff get to productive 3x faster – less senior-team interruption. We don't promise tenfold lifts because we don't see them outside of marketing decks.

What if our Kerikeri 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 knowledge base specifically, we typically run that work on Claude, Pinecone, Vercel AI SDK, Postgres, MCP and assume messy starting conditions from day one.

Twenty minutes, your call.

You describe what's broken. We'll tell you what we'd actually do about it.

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