What data preparation an AI project really needs, and how to do it without overbuilding.
dgm is an independent osFoundry integration partner — not affiliated with osFoundry’s maker (OS LLC), and dgm has no completed client integrations yet.
Data preparation is where most AI projects succeed or fail. The good news: you rarely need to fix all your data — just the data the project needs. Here is how.
What preparation really means
For most AI projects, preparation means making the specific data the use case needs accessible, reasonably clean and well-described — not a company-wide data overhaul.
A focused approach
Identify the data the use case needs, assess its quality, fix what matters for that use case, and document it. Over-building data infrastructure before a use case is a common waste.
The Australian layer
Where the data includes personal information, apply the Privacy Act — minimise what you use, and decide residency for sensitive data. osFoundry’s managed cloud pins data to the US, EU or Japan — it does not currently offer an Australian managed region. For data that must stay in Australia, the honest path is self-hosting osFoundry (BYO Cloud) inside an Australian cloud region such as AWS (Sydney or Melbourne), Microsoft Azure (Australia East, Australia Southeast or Australia Central in Canberra) or Google Cloud (Sydney or Melbourne), or running models locally on-device.
Where dgm fits
dgm is an independent integration partner that helps Australian businesses adopt osFoundry — scoping a first use case, handling the build, and connecting AI to the systems you already run. dgm is independent of osFoundry’s maker (OS LLC) and has no completed client integrations yet, so everything described here is a service offered, not a past result. If you want to scope a practical first project, dgm can help you map it out.