Semantic search (RAG) in Taupō.

For Taupō operators who want a working pilot in weeks, not a year-long programme.

Semantic search (RAG) for a Taupō operator

Honest scoping before we quote a cent. If we don't think we can move the needle, we'll tell you on the first call.

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 Taupō 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

We've worked with enough operators in Taupō to know that the brief that arrives in our inbox is rarely the brief that ends up shipped. The first thing we do on any semantic search (RAG) project is sit with your team for a day before we propose anything.

If we build the right slice first, Taupō teams feel the difference inside the first month. Average search time drops from 6 minutes to 12 seconds.

Why Taupō businesses are a fit for this.

Hospitality, accommodation, adventure tourism, and trades supporting a building boom. AI helps the small-team operators look big.

We work with teams in

CBDAcacia BayKinlochTurangiWhakatane

What we build

Semantic search (RAG), tailored to Taupō businesses.

Built on: PineconeClaudePostgres pgvectorVercel AI SDK

Common questions

Before you book the call.

When does semantic search (RAG) actually pay back? +

Inside the first quarter, in our experience. We pick the first slice specifically because it's the highest-leverage workflow for a Taupō – so the savings start landing before the rest of the build is finished.

Do you do hourly billing or fixed price? +

Fixed price for the pilot, every time. After that it's your call – fixed price per milestone or a small monthly retainer for ongoing iteration. We don't run open-ended T&M because it disincentivises us from finishing.

Has this actually shipped for a real Taupō? +

Yes. Average search time drops from 6 minutes to 12 seconds. We'll share comparable engagements on the call.

Will this run on our own infrastructure? +

Yes, where it makes sense. Semantic search (RAG) can sit entirely in your cloud account, with model calls routed through endpoints you control. We default to Pinecone, Claude, Postgres pgvector, Vercel AI SDK but the architecture supports your existing platform choices.

Skip the pitch.

Tell us the workflow and we'll come back with what we'd build first.

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