Plumbing businesses are some of the most efficient operators in New Zealand – which means the easy wins from semantic search (RAG) are usually already taken. The brief we accept is the one focused on the workflow you've tried to fix twice and given up on.
Plumbing businesses · Applied AI
For plumbing businesses who want results in weeks, not a year-long transformation programme.
What semantic search (RAG) actually does
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.
- 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
Built on: Pinecone Claude Postgres pgvector Vercel AI SDK
Without Kiwi Dynamics
With Kiwi Dynamics
What gets in the way
The friction plumbing businesses hit that other industries don't.
- Plumbers lose jobs to whoever answers the phone first, and most calls come in while they're already under a sink.
- Missed calls, slow quotes, and unchased invoices are the three leaks that cost plumbing businesses the most money.
How we build semantic search (RAG) for plumbing businesses.
We scope narrow, ship a working pilot, then harden it into production. The first slice is the highest-leverage workflow for a plumbing business business, so value lands before the build is finished. AI search over your data.
Talk to usThe outcome for plumbing businesses
We'd call the engagement a success when plumbing businesses are using the system without thinking about us. Average search time drops from 6 minutes to 12 seconds.
Not your typical AI agency.
Honest about what AI can and cannot do
Ships the one workflow that pays for itself
Hours given back, never the size of the invoice
*Every engagement is scoped and quoted up front. Results vary by workflow and business.
Questions
FAQ
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 plumbing business?
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.
Anyone else in this space using semantic search (RAG)?
Plenty. Average search time drops from 6 minutes to 12 seconds. The interesting question is rarely "does it work" – it's "is your team ready to use the output." That's what we'd scope 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 plumbing business team can actually run after we hand the build over, not what looks good on a vendor sticker.
One short call.
Tell us what you're trying to fix. We'll come back inside a working day.
Get in touch
Talk to us about this
Tell us what you're trying to do and we'll reply with how we'd build it — no obligation.