Quick answerOffering an enterprise customer a bring-your-own-model or private-deployment option means running your agent on infrastructure or against a model choice you do not fully control, which raises governance questions your standard SaaS agreement was not written for: which support and reliability commitments still hold when the model or infrastructure is theirs, how you version and patch an agent you cannot push updates to on your own schedule, what data residency and compliance posture actually changes, and what commercial terms reflect the extra engineering and support cost of a non-standard deployment. This is a different question from build-versus-buy, which is about whether you build the agent at all, and from usage metering, which is about how you charge once the deployment model is already settled.
Why this is not a pricing question in disguise
It is tempting to fold bring-your-own-model requests into a pricing conversation, since enterprise customers often ask for it alongside a bigger contract. Resist that framing. The commercial terms are downstream of a set of technical and support commitments that have to be settled first: what you are actually agreeing to support changes fundamentally when the customer controls the model or the infrastructure, independent of what you charge for it.
Technical governance: what you can no longer assume
On your own infrastructure, you control model version, latency, and uptime directly. On a customer's infrastructure or with their chosen model, you are dependent on a system you cannot patch, roll back, or monitor with your usual tooling. Before agreeing to this, define explicitly: which model providers and versions you actually support (not "any model," a bounded, tested list), a minimum infrastructure and API compatibility bar the customer's environment must meet, and a clear line on what you will and will not debug when a failure could originate on either side of that boundary. This overlaps with the compliance groundwork in Which Compliance Frameworks Actually Apply to Your AI Agent (SOC 2, HIPAA, GDPR), since a private deployment often exists specifically to satisfy one of those frameworks, and the technical governance terms need to actually deliver the compliance posture the customer is buying it for.
Data residency and sovereignty do not automatically resolve themselves
A private or on-customer-infrastructure deployment is frequently requested specifically to solve a data residency requirement, but running your agent on the customer's infrastructure does not automatically mean their data never leaves their jurisdiction; it depends on what your agent still calls back to, such as a shared logging pipeline, an update service, or a shared vector store. Map every call your deployed agent makes outward, the same discipline covered in How to Handle Data Residency and Sovereignty When Your AI Agent's Model Provider Is Abroad, and confirm the private-deployment offering actually closes the residency gap rather than just moving it one layer down.
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Support commitments have to be renegotiated, not assumed to carry over
Your standard support SLA almost certainly assumes you can inspect logs, push a hotfix, and reproduce an issue on infrastructure you control. None of that is guaranteed on a customer's own environment. Write a separate support addendum for private deployments that states plainly what level of access the customer must grant for you to debug an issue, what happens when they will not grant it, and how vendor due diligence changes when your product is now, in effect, software the customer partially operates themselves, echoing the review discipline in Due Diligence on Your AI Agent Vendor's Subprocessors but pointed at your own deployment rather than a subprocessor's.
Commercial terms follow the engineering reality, not the other way around
Once the technical and support scope is defined, price it to reflect the real cost: private and bring-your-own-model deployments typically carry meaningfully higher implementation and ongoing support cost than standard SaaS delivery, and the contract should say so explicitly rather than treating it as a checkbox add-on to an existing plan.
FAQ
Should every enterprise customer be offered this option? No, reserve it for accounts where the request is driven by a real compliance or data-sovereignty requirement you have verified, since the support and engineering cost is real and not worth absorbing for a preference alone.
Who owns an incident when the failure could be on either side of the infrastructure boundary? Define this in the support addendum before it happens: a shared triage step to establish which side the failure originated on, with a default assumption (commonly, the vendor triages first for anything touching the agent's own logic) so the customer is never stuck without an owner.
Does bring-your-own-model change what we charge? It usually should, since supporting a wider, less predictable set of model providers and infrastructure configurations carries real ongoing engineering cost that a standard-deployment price was never built to cover.