Burnie sits in a regional context that genuinely changes the build. Connectivity assumptions, the rhythm of the working week, the proximity of your team to your customers - none of those are details our default AI data analytics template would catch.
Ask your data in English - wired into a Burnie workflow, not bolted on the side.
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 Burnie teams tell us when they get on a call.
- Burnie is a port and industrial town on the north west coast, running on forestry, mining services and manufacturing.
- Bulk port operations, forestry, mineral processing and advanced manufacturing. Industrial clients bring safety and quality documentation that small suppliers struggle to keep up with.
We work with teams across Burnie: Burnie CBD · Somerset · Wynyard · Upper Burnie · Penguin.
Talk to us about this →
How we build AI data analytics for a Burnie team.
We scope narrow, ship a working pilot, then harden it into production. The first slice is the highest-leverage workflow for your Burnie business, so value lands before the build is finished. Ask your data in English.
Talk to usThe outcome for Burnie teams
Owners check the business in 2 minutes instead of 2 hours. For Burnie 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
*Every engagement is scoped and quoted up front. Results vary by workflow and business.
FAQ
How fast could we have AI data analytics in production?
Eight to ten weeks for most Burnie 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's the smallest engagement you'd take on?
A two-week paid discovery for Burnie businesses that aren't sure whether the build is worth doing at all. You get a one-page write-up of what we'd build, what we'd skip, and what it would cost. About 30% of those discoveries end with us recommending you don't proceed.
Do you have proof this works for Burnie businesses?
Direct case study: Owners check the business in 2 minutes instead of 2 hours. Happy to walk you through full numbers on a call.
What if our Burnie 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 AI data analytics specifically, we typically run that work on DuckDB, Claude, Metabase, BigQuery, Vercel AI SDK and assume messy starting conditions from day one.
One reply, one direction.
We don't run sequences or follow-up automation. One useful answer, one decision on your side.
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.