01
Where documents live
Cloud AI: your documents (or fragments of them) transit to a third-party API. Private AI: documents never leave your infrastructure — there is no external transit to secure or explain.
Private AI vs Cloud AI
Private AI vs Cloud AI: What Regulated Teams Should Actually Compare.
Both approaches use similar underlying models. The difference that matters for regulated document work isn't model quality — it's where your documents go, who can see them, and what you can prove about it.
01
The comparison people mean to make, and the one they actually need to.
Most "AI comparison" conversations focus on which model answers better. For teams handling confidential contracts, batch records, or audit evidence, that's the wrong first question. The first question is where the document goes the moment you ask it something — and whether you can show a regulator, a client, or your own security team exactly what happened to it.
02
Six differences that actually matter.
02
What you can tell an auditor
Cloud AI: you are relying on a vendor's data-handling policy and hoping it satisfies your regulator. Private AI: you can show the deployment itself, on your own servers, under your own access controls.
03
Offline and air-gapped operation
Cloud AI requires a live connection to the provider by definition. Private AI can run with no internet route out at all, where that's a requirement.
04
Cost shape
Cloud AI: per-token or per-seat fees that scale with usage indefinitely. Private AI: infrastructure and deployment investment up front, then usage that doesn't generate a recurring per-query bill.
05
Model choice and lock-in
Cloud AI ties you to one provider's model and roadmap. Private AI deployments are typically model-agnostic — open-weight models you can evaluate, swap, or fine-tune under your own governance.
06
What it costs to get wrong
For a marketing draft, cloud AI's tradeoffs are usually fine. For a batch record, a client contract, or a regulatory dossier, the tradeoff isn't convenience — it's exposure.
03
When cloud AI is the right call.
We're not going to tell you private AI is always the answer.
If your documents aren't confidential and your workflow doesn't touch regulated data, a cloud AI tool is often faster to adopt and cheaper to start with. Private AI earns its cost when the documents themselves are the risk: client files, batch records, audit evidence, unreleased research, anything you'd need to explain to a regulator or a client if it left the building.
See It On Your Documents
Not sure which side of this you're on?
Tell us what you're working with — we'll give you a straight answer, including if the answer is "cloud AI is fine for this."