Building companies 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.
Building companies · Applied AI
For building companies 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 building companies hit that other industries don't.
- Builders run multiple sites at once, and the paperwork behind each one grows faster than anyone has time to manage.
- Variations, supplier orders, and client updates are the admin layer that determines whether a build stays on schedule.
How we build semantic search (RAG) for building companies.
We scope narrow, ship a working pilot, then harden it into production. The first slice is the highest-leverage workflow for a building company business, so value lands before the build is finished. AI search over your data.
Talk to usThe outcome for building companies
We'd call the engagement a success when building companies 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 fast could we have semantic search (RAG) in production?
Eight to ten weeks for most building companies. 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's the smallest engagement you'd take on?
A two-week paid discovery for building companies that aren't sure whether the build is worth doing at all. You get a one-page write-up of what we'd build, what we'd skip, and what it would cost. About 30% of those discoveries end with us recommending you don't proceed.
Do you have proof this works for building companies?
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 building company 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.
One reply, one direction.
We don't run sequences or follow-up automation. One useful answer, one decision on your side.
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.