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 semantic search (RAG) template would catch.
Northland · Applied AI
Semantic search (RAG) designed around the way a Kerikeri team actually runs.
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
Without Kiwi Dynamics
With Kiwi Dynamics
Northland
What Kerikeri teams tell us when they get on a call.
- 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 semantic search (RAG) 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. AI search over your data.
Talk to usThe outcome for Kerikeri teams
The shape of the result for Kerikeri teams: Average search time drops from 6 minutes to 12 seconds. Built on Pinecone, 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
*Every engagement is scoped and quoted up front. Results vary by workflow and business.
Questions
FAQ
How fast could we have semantic search (RAG) 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 does semantic search (RAG) cost for a Kerikeri?
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 Kerikeri 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 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 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.
One reply, one direction.
We don't run sequences or follow-up automation. One useful answer, one decision on your side.
Get in touch
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.