Semantic search (RAG) in Whakatāne.
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 Whakatāne 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
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.
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.
The pattern across Whakatāne engagements we've shipped.
Kiwifruit, aquaculture, marine tourism, and a strong iwi economy. AI tools that work offline and bilingually find their home here.
We work with teams in
What we build
Semantic search (RAG), tailored to Whakatāne 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 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.