Semantic search (RAG) is overhyped at the macro level and underused at the workflow level. For a NZ auto repair shop, that gap is where the actual ROI lives – and where most of our work happens.
Auto repair shops · Applied AI
Semantic search (RAG) that fits a auto repair shop's week, not the other way around.
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
The honest read
Where most auto repair shops engagements actually deliver value.
- Mechanics quote from underneath a car and answer the phone from underneath a car, and one of those always loses.
- Booking, quoting, and parts follow-up are the admin layer that decides how many cars a workshop can turn over in a week.
How we build semantic search (RAG) for auto repair shops.
We scope narrow, ship a working pilot, then harden it into production. The first slice is the highest-leverage workflow for a auto repair shop business, so value lands before the build is finished. AI search over your data.
Talk to usThe outcome for auto repair shops
What changes for auto repair shops after this lands: the work that used to need a person stays done, the work that needs a person gets done with their attention undivided. 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
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 auto repair shop – so the savings start landing before the rest of the build is finished.
How do you price semantic search (RAG) engagements?
Fixed-scope pilots first, then either project pricing or a small monthly retainer for the ongoing work. No long lock-ins, no 18-month black-box deals. Most auto repair shops are surprised how small the first cheque is.
Has this actually shipped for a real auto repair shop?
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.
Worth a conversation?
Even if you don't end up working with us, you'll leave the call knowing what's worth building.
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.