Northern Territory · Applied AI
Semantic search (RAG) in Darwin
AI search over your data, built for businesses operating in Darwin.
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.
We've worked with enough operators in Darwin 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.
- 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
Why Darwin businesses choose this
Darwin runs on defence, resources and a tourism season split hard by the wet – AI here means handling seasonal swings without carrying seasonal headcount.
The Darwin context, plainly.
A major defence presence, gas and resources projects, and a tourism trade that lives and dies by the dry season. Darwin businesses want AI that scales staffing-heavy work up and down without the overhead of actually hiring for it.
We work with teams across Darwin: Darwin CBD · Palmerston · Casuarina · Nightcliff · Parap · Stuart Park.
How we build semantic search (RAG) for a Darwin team
We scope narrow, ship a working pilot, then harden it into production. The first slice is the highest-leverage workflow for your Darwin business, so value lands before the build is finished. Every engagement starts with a short call and a paid discovery if the brief needs one.
AI search over your data.
The outcome for Darwin teams
The shape of the result for Darwin teams: Average search time drops from 6 minutes to 12 seconds. Built on Pinecone, hardened with the rest of the stack as it scales.
Average search time drops from 6 minutes to 12 seconds.
Semantic search (RAG) in Darwin – common questions
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 Darwin – 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 Darwin businesses are surprised how small the first cheque is.
Has this actually shipped for a real Darwin?
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.
The honest version of a sales call.
No deck. No discovery doc. Just whether this is worth building and what it would cost.
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.