Semantic search (RAG) in Rotorua.
Semantic search (RAG) that lives in your stack, not on a vendor's roadmap. Shipped from Bay of Plenty.
What this is
AI search over your data
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.
Average search time drops from 6 minutes to 12 seconds.
How it helps your Rotorua team
What you actually get.
- Indexes Drive, SharePoint, Notion, Slack, your CRM
- Returns answers with source links – no hallucinations
- Permissioned so staff only see what they should
- Re-indexes nightly so results stay fresh
Rotorua 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 changes for Rotorua teams 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. Average search time drops from 6 minutes to 12 seconds.
Our field notes from Rotorua builds.
From iwi-owned enterprises to international tour operators, Rotorua businesses want AI that handles peaks without flattening the manaakitanga.
We work with teams in
What we build
Semantic search (RAG), tailored to Rotorua businesses.
- 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
Common questions
Before you book the call.
What's the realistic timeline for semantic search (RAG) with a Rotorua? +
Most Rotorua businesses 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 semantic search (RAG) worth it for a smaller Rotorua? +
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.
Do you have proof this works for Rotorua 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 happens if we want to swap a vendor out later? +
Semantic search (RAG) 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. Pinecone, Claude, Postgres pgvector, Vercel AI SDK 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.
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