Most of our Newcastle engagements start the same way: a 20-minute call where the owner describes a workflow we've heard before in shape but never in detail. AI data analytics is then designed against the detail, not the shape.
Built and supported here - the way a Newcastle business would actually use it.
Our goal is to give Newcastle businesses a three-day weekend, so people can spend more time with their families and the people they love :)
What AI data analytics actually does
Stop digging through dashboards. Ask plain-English questions of your sales, jobs, and customer data - get charts, summaries, and the why behind the numbers in seconds.
- 01 Natural-language queries over your Xero, Shopify, CRM data
- 02 Weekly auto-summaries delivered to inbox or Slack
- 03 Anomaly detection - flags weird weeks before you notice
- 04 Forecasts that explain themselves, not black boxes
Built on: DuckDB Claude Metabase BigQuery 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 AI data analytics 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 Newcastle 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 AI data analytics 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 Newcastle context, plainly.
- Newcastle's port, energy and manufacturing base is shifting fast toward renewables and advanced manufacturing - AI here means keeping a lean team ahead of that transition.
- The world's largest coal export port sits alongside a growing renewable energy and advanced manufacturing sector. Newcastle businesses want practical automation for logistics, quoting and reporting, not a research project.
We work with teams across Newcastle: Newcastle CBD · Hamilton · Charlestown · Maitland · Mayfield · Lake Macquarie.
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How we build AI data analytics for a Newcastle team.
We scope narrow, ship a working pilot, then harden it into production. The first slice is the highest-leverage workflow for your Newcastle business, so value lands before the build is finished. Ask your data in English.
Talk to usHow the work runs
- Find the one workflowWe look for the job costing Newcastle 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 Newcastle teams
The shape of the result for Newcastle teams: Owners check the business in 2 minutes instead of 2 hours. Built on DuckDB, 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 AI data analytics 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 Newcastle - so the savings start landing before the rest of the build is finished.
How do you price AI data analytics 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 Newcastle businesses are surprised how small the first cheque is.
Anyone else in this space using AI data analytics?
Plenty. Owners check the business in 2 minutes instead of 2 hours. The interesting question is rarely "does it work" - it's "is your team ready to use the output." That's what we'd scope on the call.
Will this run on our own infrastructure?
Yes, where it makes sense. AI data analytics can sit entirely in your cloud account, with model calls routed through endpoints you control. We default to DuckDB, Claude, Metabase, BigQuery, 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.