We've worked with enough operators in Darwin to know that the brief that arrives in our inbox is rarely the brief that ends up shipped. The first thing we do on any semantic search (RAG) project is sit with your team for a day before we propose anything.
AI search over your data, built for businesses operating in Darwin.
Our goal is to give Darwin businesses a three-day weekend, so people can spend more time with their families and the people they love :)
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
What you actually get
Every engagement is scoped and quoted up front. This is what is in the box.
- A working pilot, in productionNot a prototype on someone's laptop. The first slice of semantic search (RAG) runs against real work within weeks.
- Your data stays yoursIt runs on your accounts and your tools. If we part ways you keep the system and everything in it.
- The workflow mapped before codeWe write down what good looks like for Darwin businesses first, so nobody is guessing at handover.
- Support after it landsThe people who built it stay reachable when the business changes shape around it.
How semantic search (RAG) compares
The two things most businesses do instead, and where each one runs out.
| Hiring for it | An off-the-shelf tool | Koala Dynamics | |
|---|---|---|---|
| Fit to how you work | Fits perfectly, costs a salary | You bend your process to suit the tool | Built around the workflow you already run |
| Time to something useful | Immediate, and permanent | Quick to switch on, slow to make fit | A working slice in weeks, then hardened |
| Who owns the data | You do | The vendor, on the vendor's terms | You do, in your own accounts |
| When it breaks | That person sorts it, if they are in | A support queue and a ticket number | The people who built it |
| What it costs | A salary, every year, forever | Per seat, forever, used or not | Scoped and quoted up front |
The Darwin context, plainly.
- Darwin runs on defence, resources and a tourism season split hard by the wet - AI here means handling seasonal swings without carrying seasonal headcount.
- A major defence presence, gas and resources projects, and a tourism trade that lives and dies by the dry season. Darwin businesses want AI that scales staffing-heavy work up and down without the overhead of actually hiring for it.
We work with teams across Darwin: Darwin CBD · Palmerston · Casuarina · Nightcliff · Parap · Stuart Park.
Talk to us about this →
How we build semantic search (RAG) for a Darwin team.
We scope narrow, ship a working pilot, then harden it into production. The first slice is the highest-leverage workflow for your Darwin business, so value lands before the build is finished. AI search over your data.
Talk to usHow the work runs
- Find the one workflowWe look for the job costing Darwin businesses the most hours or the most leads, and deliberately ignore the rest for now.
- Ship a working sliceA narrow version goes into production in weeks, against real work, so the value shows up before the build is finished.
- Prove it, then widenWe measure it against what the work cost before. If it does not pay for itself, we say so rather than scaling it.
- Harden and hand overLogging, fallbacks and a real handover, so it keeps running when we are not in the room.
The outcome for Darwin teams
The shape of the result for Darwin 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
When does semantic search (RAG) actually pay back?
Inside the first quarter, in our experience. We pick the first slice specifically because it's the highest-leverage workflow for a Darwin - so the savings start landing before the rest of the build is finished.
How do you price semantic search (RAG) engagements?
Fixed-scope pilots first, then either project pricing or a small monthly retainer for the ongoing work. No long lock-ins, no 18-month black-box deals. Most Darwin businesses are surprised how small the first cheque is.
Has this actually shipped for a real Darwin?
Yes. Average search time drops from 6 minutes to 12 seconds. We'll share comparable engagements on the call.
Will this run on our own infrastructure?
Yes, where it makes sense. Semantic search (RAG) can sit entirely in your cloud account, with model calls routed through endpoints you control. We default to Pinecone, Claude, Postgres pgvector, Vercel AI SDK but the architecture supports your existing platform choices.
The honest version of a sales call.
No deck. No discovery doc. Just whether this is worth building and what it would cost.
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.