Dubbo businesses don't need another generic AI pitch. Semantic search (RAG) only earns its keep when it's built around the workflow you actually run on a wet Tuesday, and that's how we scope every engagement we take on in New South Wales.
Semantic search (RAG) that lives in your stack, not on a vendor's roadmap. Shipped from New South Wales.
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 Koala Dynamics
With Koala Dynamics
Our field notes from Dubbo builds.
- Dubbo is the service hub for the Orana - agriculture, transport, health and government all radiate out of it across an enormous catchment.
- A logistics and agricultural service centre covering western NSW, plus a base hospital and a large tourism draw. Businesses serve customers hundreds of kilometres out, so remote quoting and scheduling carry disproportionate weight.
We work with teams across Dubbo: Dubbo CBD · Delroy · West Dubbo · South Dubbo · Wellington.
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How we build semantic search (RAG) for a Dubbo team.
We scope narrow, ship a working pilot, then harden it into production. The first slice is the highest-leverage workflow for your Dubbo business, so value lands before the build is finished. AI search over your data.
Talk to usThe outcome for Dubbo teams
The shape of the result for Dubbo teams: Average search time drops from 6 minutes to 12 seconds. Built on Pinecone, hardened with the rest of the stack as it scales.
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.
FAQ
How fast could we have semantic search (RAG) in production?
Eight to ten weeks for most Dubbo businesses. 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 Dubbo businesses 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.
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 if our Dubbo 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 short call.
Tell us what you're trying to fix. We'll come back inside a working day.
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.