The version of AI data analytics that works for a Orange business is rarely the version a national vendor would sell you. We build the one that fits how your team actually operates - usually with fewer parts than the off-the-shelf pitch.
Built and supported here - the way a Orange business would actually use it.
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
The Orange context, plainly.
- Orange runs on agriculture, cool-climate wine, gold mining at Cadia and a regional health sector, which is an unusually diverse mix for a city its size.
- Cadia gold mine, a strong horticulture and wine sector, and a base hospital that serves the Central West. The services businesses here juggle mining clients on procurement terms and farm clients on a season, and both need different handling.
We work with teams across Orange: Orange CBD · Glenroi · Bletchington · Calare · Millthorpe.
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How we build AI data analytics for a Orange team.
We scope narrow, ship a working pilot, then harden it into production. The first slice is the highest-leverage workflow for your Orange business, so value lands before the build is finished. Ask your data in English.
Talk to usThe outcome for Orange teams
We'd call the engagement a success when Orange teams are using the system without thinking about us. Owners check the business in 2 minutes instead of 2 hours.
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 Orange - so the savings start landing before the rest of the build is finished.
Do you do hourly billing or fixed price?
Fixed price for the pilot, every time. After that it's your call - fixed price per milestone or a small monthly retainer for ongoing iteration. We don't run open-ended T&M because it disincentivises us from finishing.
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.