Governed LLM access: buy the platform or build on the cloud
Written from the Japanese enterprise context, where governed access is usually the trigger for the project.
AI Tools Hub Editorial · published · updated
The actual problem
It is not capability. It is a hundred employees each holding a personal AI subscription: no audit trail, no enforceable policy, and no answer to the question of where company data went.
Comparison
| Domestic SaaS | Build on Azure OpenAI | |
|---|---|---|
| Setup | None | Weeks to months |
| Monthly | Flat per seat | Token metered plus platform operations |
| Admin console | Included | Build it |
| Document search | Connectors included | Build it |
| New model features | Wait for the vendor | Available immediately |
| Staff required | An operator | Engineers |
Build looks cheap because the labour is not counted
Admin console, permissions, usage visibility, keeping the document index current — if you cannot name the person who owns that work, buying is cheaper in total even where the token arithmetic says otherwise.
Search quality is a document problem
Either path inherits the state of your document store. If the superseded version of a policy is still filed next to the current one, the system will cite the old one confidently. Fix the corpus before choosing the vendor.
FAQ
Which should we try first?
SaaS. A month of real usage data makes the build-versus-buy estimate far more accurate than any up-front analysis.