Australian Capital Territory · Applied AI
Semantic search (RAG) in Canberra
Semantic search (RAG) designed around the way a Canberra team actually runs.
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.
Canberra 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 Australian Capital Territory.
- 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 Canberra businesses choose this
Canberra runs on government, policy and the contractors that service them – AI here has to handle process and compliance as carefully as it handles speed.
Our field notes from Canberra builds.
Federal departments and the consultancies orbiting them generate huge volumes of documents, submissions and reporting. Canberra teams want AI that speeds up drafting and research without ever guessing on something that needs a citation.
We work with teams across Canberra: Civic · Belconnen · Woden · Gungahlin · Tuggeranong · Barton.
How we build semantic search (RAG) for a Canberra team
We scope narrow, ship a working pilot, then harden it into production. The first slice is the highest-leverage workflow for your Canberra 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 Canberra teams
If we build the right slice first, Canberra teams feel the difference inside the first month. Average search time drops from 6 minutes to 12 seconds.
Average search time drops from 6 minutes to 12 seconds.
Semantic search (RAG) in Canberra – common questions
How fast could we have semantic search (RAG) in production?
Eight to ten weeks for most Canberra 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 does semantic search (RAG) cost for a Canberra?
Pilots start from a fixed scope priced to land a measurable result inside 6 weeks. Pricing depends on data volume, integration complexity, and whether you need us on managed services afterwards. We'll quote precisely after a 30-minute scoping call.
Can you walk us through a comparable build?
Yes – on the first call we'll pick the closest engagement we've shipped to what you're describing and walk through the outcome, the headcount and the time it took. Average search time drops from 6 minutes to 12 seconds.
What if our Canberra 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.
Sketch this with us.
We'll map your real workflow before quoting anything.
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.