How to build an internal AI chatbot over company knowledge while keeping data in-country.
dgm is an independent osFoundry integration partner — not affiliated with osFoundry’s maker (OS LLC), and dgm has no completed client integrations yet.
An internal AI chatbot that answers from your company knowledge is a high-value, achievable first project. Here is how to build one in Canada.
What it does
An internal chatbot retrieves answers from your policies, docs and knowledge bases so staff get accurate, sourced answers instead of hunting through files. Grounding it in your data (RAG) keeps answers specific.
Building it
Connect your knowledge sources, set up retrieval, choose a model, and add access controls. Keep a feedback loop so answers improve. Start with one well-defined knowledge area.
Canadian considerations
Internal knowledge often includes personal or confidential data, so apply PIPEDA and Law 25, control access, and decide residency. osFoundry’s managed cloud pins data to US, EU or Japan — it does not currently offer a Canadian managed region. For data that must stay in Canada, the honest path is self-hosting osFoundry (BYO Cloud) inside a Canadian cloud region such as AWS Canada (Montréal/Calgary), Azure (Toronto/Quebec City) or Google Cloud (Montréal), or running models locally on-device.
Where dgm fits
dgm is an independent integration partner that helps Canadian 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.