Private AI infrastructure vs Microsoft Copilot
Copilot is not a bolt-on chatbot. It's woven into Word, Excel, Outlook, Teams, and the rest of Microsoft 365, and for many organizations that integration is the entire point, it can read a document, summarize a thread, and draft a reply without you copying anything anywhere. Microsoft has also published commercial data protection commitments for Copilot that are more substantial than what a typical free consumer AI tool offers. None of that changes the basic fact that Microsoft, a third party, still processes what you type into it. Whether that matters depends on what you're typing.
What Copilot's enterprise protections actually cover
Microsoft publishes commercial data protection terms for Microsoft 365 Copilot covering how prompts and responses are handled, including commitments around not using that content to train its foundation models for other customers. The specifics, exactly what's covered, what's retained, for how long, and under which licensing tier, change over time and vary by product (Copilot in Microsoft 365 versus Copilot Studio versus other Copilot surfaces aren't identical). We're not going to restate a specific clause here and risk it being stale by the time you read this; Microsoft's own Copilot trust and transparency documentation is the source to check for the current terms that apply to your tenant and licensing tier.
What's fair to say in general: for an organization mainly worried about employees using unmanaged, personal AI tools with company data, Copilot's enterprise terms and admin controls, tenant isolation, compliance boundary settings, integration with Microsoft Purview for data governance, are a meaningfully different posture than a consumer chatbot. It's a legitimate answer to that specific problem.
What doesn't change: Microsoft is still in the loop
Copilot's enterprise commitments are about how your data is handled once it reaches Microsoft's infrastructure, not about whether it reaches Microsoft's infrastructure at all. A prompt to Copilot leaves your tenant boundary conceptually even if it stays within Microsoft's cloud, and processing happens on infrastructure Microsoft operates and controls, not infrastructure you control. For most use cases that's a distinction without a practical difference. For a specific category of workload, client data under an NDA that names where processing may occur, regulated data under a residency requirement, anything where your own contract or your regulator asks "which entity has access to this data," it's the difference that decides whether you're compliant.
What changes with a dedicated Spark
A GPUwerk Spark is a dedicated NVIDIA DGX Spark, 128GB unified memory, running the model you choose, with no other tenant on the machine. Nothing you send it passes through a third party's infrastructure or is subject to a vendor's data-handling terms, because there's no vendor in the data path beyond hosting the hardware itself. At $0.79/hour single-node or $1.79/hour for a two-node cluster, it's straightforward to reason about, and it doesn't require Microsoft 365 licensing to use, though there's also no Word or Excel integration out of the box; that's something you build if you need it, not something you get for free the way Copilot's integration comes bundled.
That's the real tradeoff. Copilot's integration into the tools your team already uses every day is a genuine product advantage that a self-hosted model doesn't replicate without work. A dedicated Spark gives you a general-purpose endpoint with nobody else in the loop, but you're responsible for connecting it to whatever workflow needs it.
Where the line usually falls
Most organizations that use both draw the line by data sensitivity rather than picking one tool for everything. General drafting, meeting summaries, and day-to-day Office work through Copilot is a reasonable default, the integration is worth it and the enterprise terms cover the risk for that category of data. Anything with a contractual or regulatory restriction on where it can be processed, client-identifiable data, source code under an NDA, health or financial records under a specific compliance regime, belongs on infrastructure where the answer to "who else can see this" is nobody, because it's yours. If EU data residency specifically is the driver for you, our EU data residency post covers that in more depth. If you're weighing a private deployment for even a subset of your workloads, private LLM hosting has the specifics on what running it day to day looks like.
What you give up by moving a workload off Copilot
It's worth being honest about the other side of the trade. Copilot's awareness of what's already in the document you're editing or the thread you're reading is a real product capability that took Microsoft substantial engineering effort to build, and a self-hosted model doesn't replicate it for free. Move a workload off Copilot onto a dedicated Spark and you get raw model access, not a drop-in replacement, wiring it into the document or email context it needs is integration work you now own. For a team without spare engineering time for that plumbing, keeping general office work on Copilot even after moving specific data categories off it is a reasonable, deliberate choice rather than a compromise.
The two also don't have to compete for the same budget line. Copilot is licensed per seat on top of Microsoft 365 you're likely already paying for; a Spark is billed by the hour regardless of headcount. Running both, Copilot for office-integrated general work, a Spark for the specific workloads that need to stay off Microsoft's infrastructure, is a normal setup, not an edge case, and it avoids asking one tool to do a job it wasn't built for.