The reason we take on work in Orange is that the businesses here tend to be sharper about what they want than the brief lets on. Semantic search (RAG) for a Orange team almost always ends up looking different to semantic search (RAG) for a downtown Auckland one.
AI search over your data - wired into a Orange workflow, not bolted on the side.
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 Orange builds.
- Orange runs on agriculture, cool-climate wine, gold mining at Cadia and a regional health sector, which is an unusually diverse mix for a city its size.
- Cadia gold mine, a strong horticulture and wine sector, and a base hospital that serves the Central West. The services businesses here juggle mining clients on procurement terms and farm clients on a season, and both need different handling.
We work with teams across Orange: Orange CBD · Glenroi · Bletchington · Calare · Millthorpe.
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How we build semantic search (RAG) for a Orange team.
We scope narrow, ship a working pilot, then harden it into production. The first slice is the highest-leverage workflow for your Orange business, so value lands before the build is finished. AI search over your data.
Talk to usThe outcome for Orange teams
The shape of the result for Orange 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 Orange 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 Orange 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 Orange 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.
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.