New South Wales · Applied AI
Semantic search (RAG) in Sydney
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.
Sydney 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.
- 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 Sydney businesses choose this
Sydney runs on finance, professional services and a tech scene chasing Melbourne for the national crown – AI here has to survive a genuinely competitive market, not just look good in a pitch.
What we keep seeing in Sydney.
ASX-listed HQs, the big four banks, and a startup corridor from Surry Hills to Chippendale sit alongside a huge professional services layer of legal, accounting and consulting firms. Sydney businesses have already tried AI once, so we build for teams who want the second attempt to actually stick.
We work with teams across Sydney: CBD · North Sydney · Parramatta · Surry Hills · Chatswood · Sydney Olympic Park.
How we build semantic search (RAG) for a Sydney team
We scope narrow, ship a working pilot, then harden it into production. The first slice is the highest-leverage workflow for your Sydney 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 Sydney teams
If we build the right slice first, Sydney 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 Sydney – common questions
How fast could we have semantic search (RAG) in production?
Eight to ten weeks for most Sydney 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 Sydney?
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.
Has this actually shipped for a real Sydney?
Yes. Average search time drops from 6 minutes to 12 seconds. We'll share comparable engagements on the call.
What if our Sydney 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.
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.