AI search over your data - wired into a Hobart workflow, not bolted on the side.

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

Hobart 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 Tasmania.

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

The pattern across Hobart engagements we've shipped.

  • Hobart runs on tourism, aquaculture and a small but sharp professional services scene - AI here has to work for teams that don't have a big back office to absorb a bad tool.
  • Salmon and seafood exports, a tourism season built around MONA and the wider arts scene, and a compact CBD professional layer. Hobart businesses need AI that's genuinely easy to run without dedicated IT staff.

We work with teams across Hobart: Hobart CBD · Battery Point · Glenorchy · Kingston · Sandy Bay · Moonah.

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How we build semantic search (RAG) for a Hobart team.

We scope narrow, ship a working pilot, then harden it into production. The first slice is the highest-leverage workflow for your Hobart 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 Hobart teams

Average search time drops from 6 minutes to 12 seconds. For Hobart teams, that almost always shows up as fewer interruptions and a calmer week, not a dashboard chart.

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

What's the realistic timeline for semantic search (RAG) with a Hobart?

Most Hobart businesses have their first usable slice in week 5 or 6. We'd rather ship narrow and real than broad and aspirational - your team gets to use the thing well before the engagement is "done".

What does semantic search (RAG) cost for a Hobart?

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.

Do you have proof this works for Hobart businesses?

Direct case study: Average search time drops from 6 minutes to 12 seconds. Happy to walk you through full numbers on a call.

What happens if we want to swap a vendor out later?

Semantic search (RAG) is built behind a small adapter layer specifically so swapping a model provider or a data source is a one-day job, not a re-architecture. Pinecone, Claude, Postgres pgvector, Vercel AI SDK are our defaults, but the build is intentionally portable.

Sketch this with us.

We'll map your real workflow before quoting anything.

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.