Semantic search (RAG) that lives in your stack, not on a vendor's roadmap. Shipped from New South Wales.

Our goal is to give Sydney businesses a three-day weekend, so people can spend more time with their families and the people they love :)

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.

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

What you actually get

Every engagement is scoped and quoted up front. This is what is in the box.

How semantic search (RAG) compares

The two things most businesses do instead, and where each one runs out.

 Hiring for itAn off-the-shelf toolKoala Dynamics
Fit to how you workFits perfectly, costs a salaryYou bend your process to suit the toolBuilt around the workflow you already run
Time to something usefulImmediate, and permanentQuick to switch on, slow to make fitA working slice in weeks, then hardened
Who owns the dataYou doThe vendor, on the vendor's termsYou do, in your own accounts
When it breaksThat person sorts it, if they are inA support queue and a ticket numberThe people who built it
What it costsA salary, every year, foreverPer seat, forever, used or notScoped and quoted up front

What we keep seeing in Sydney.

  • 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.
  • 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.

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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. AI search over your data.

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How the work runs

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.

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

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*Every engagement is scoped and quoted up front. Results vary by workflow and business.

How much is not automating costing you?

Nine hours a week of admin is 468 hours a year. With Koala Dynamics, that drops to about 52.

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*Based on 9 hours a week of admin at Koala Dynamics' typical 80% automation rate. Your number may vary, the calculator uses your own.

FAQ

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.

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.