Customer-hosted SaaS is starting to make more sense to me than charging for every unit of usage

I've been thinking a lot about the economics of usage-based SaaS, especially for AI products.

With Voice AI, the usual model is pretty straightforward:

customer uses more minutes → platform bill keeps increasing.

But once a customer reaches meaningful volume, that starts creating a weird incentive.

The customer wants usage to become cheaper as they scale, while the platform makes more money specifically because their underlying compute/API consumption increases.

We started experimenting with a different model:

separate the software from the infrastructure.

Instead of forcing everything through the vendor's cloud, the application can also run inside the customer's AWS/Azure/GCP environment.

They own/pay for:

• cloud infrastructure
• telephony
• LLM usage
• speech providers
• their data

The software company provides:

• the application/runtime
• updates
• orchestration
• deployment tooling
• support
• governance/enterprise features

That changes the business model from:

"pay us every time the software does something"

to something closer to:

"license the software, then operate it at whatever scale makes sense for you."

There are obviously downsides.

Supporting customer infrastructure is harder.

Upgrades become more complicated.

You have to deal with different cloud environments, networking, observability, secrets, migrations and support boundaries.

But for larger customers, I'm starting to think infrastructure ownership itself can be part of the premium offering rather than the cheaper offering.

We've been exploring this while building a Voice AI platform called Elphie. Disclosure: I'm part of the team building it.

For people who've sold B2B SaaS both ways:

At what point did customer-hosted/private deployments become worth the operational complexity for you?

I'm especially curious about support burden, margins and how you handled upgrades across customer environments.