Semantic search (RAG) in Whangārei.
Semantic search (RAG) designed around the way a Whangārei team actually runs.
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 Whangārei 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
Whangārei 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.
If we build the right slice first, Whangārei teams feel the difference inside the first month. Average search time drops from 6 minutes to 12 seconds.
What we keep seeing in Whangārei.
Agriculture, marine, tourism, and trades across a wide region. AI lands when it works offline and respects the kilometres between sites.
We work with teams in
What we build
Semantic search (RAG), tailored to Whangārei 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.
How quickly can we see something running? +
Week three for a clickable internal demo against real data. Week six for a slice your team can actually use. We hold ourselves to those numbers because they're what stops a project drifting into "endless discovery".
Is semantic search (RAG) worth it for a smaller Whangārei? +
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.
Has this actually shipped for a real Whangārei? +
Yes. Average search time drops from 6 minutes to 12 seconds. We'll share comparable engagements on the call.
What tools do you build semantic search (RAG) on? +
For semantic search (RAG) we usually reach for Pinecone, Claude, Postgres pgvector, Vercel AI SDK. We're tool-agnostic at heart – we pick what your Whangārei team can actually run after we hand the build over, not what looks good on a vendor sticker.
One reply, one direction.
We don't run sequences or follow-up automation. One useful answer, one decision on your side.
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