Semantic search (RAG) in Whanganui.
Semantic search (RAG) that lives in your stack, not on a vendor's roadmap. Shipped from Manawatū-Whanganui.
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 Whanganui 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
Whanganui 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.
We'd call the engagement a success when Whanganui teams are using the system without thinking about us. Average search time drops from 6 minutes to 12 seconds.
The pattern across Whanganui engagements we've shipped.
Tourism, creative industries, and a growing remote-work population. AI tools that scale a small team's reach without enterprise overhead win.
We work with teams in
What we build
Semantic search (RAG), tailored to Whanganui 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 Whanganui? +
Most Whanganui 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".
What does semantic search (RAG) cost for a Whanganui? +
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 Whanganui 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.