Semantic search (RAG) in Hamilton.
Semantic search (RAG) that lives in your stack, not on a vendor's roadmap. Shipped from Waikato.
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 Hamilton 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
Hamilton businesses don't need another generic AI pitch. Semantic search (RAG) only earns its keep when it's built around the workflow you actually run on a wet Tuesday, and that's how we scope every engagement we take on in Waikato.
We'd call the engagement a success when Hamilton teams are using the system without thinking about us. Average search time drops from 6 minutes to 12 seconds.
What we keep seeing in Hamilton.
Dairy, agritech, transport, and a growing professional services sector. Hamilton businesses want AI that works in the ute and on the farm – not just in the office.
We work with teams in
What we build
Semantic search (RAG), tailored to Hamilton 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 Hamilton? +
Most Hamilton 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 Hamilton? +
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.
Can you walk us through a comparable build? +
Yes – on the first call we'll pick the closest engagement we've shipped to what you're describing and walk through the outcome, the headcount and the time it took. Average search time drops from 6 minutes to 12 seconds.
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 reply, one direction.
We don't run sequences or follow-up automation. One useful answer, one decision on your side.
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