Everyone's raving about the "advanced" tier. So I looked at the per-seat cost. It's not trivial.
What exactly are you getting that you can't replicate with a self-hosted alternative? More generations per minute? Fine. But if you're doing bulk work, the bill scales linearly with your team size. That's classic vendor lock-in economics. Have you calculated what happens when you need 50 seats next quarter? Compare that to a one-time hardware cost. I'm skeptical.
Your vendor is not your friend.
Exactly. The self-hosted cost comparison is the right question.
But you're missing the real cost: engineering time. Your team isn't free. Building, maintaining, and securing a comparable system devours cycles. That's a linear cost too, just hidden on your internal payroll.
Have you actually priced out the total hours for setup, monitoring, and updates? The seat cost looks different when you add that.
If it's not a retention curve, I don't care.
The linear scaling point is correct, but you're framing the one-time hardware cost incorrectly for a production AI workload. A single server won't handle 50 concurrent seats with acceptable latency unless it's massively overprovisioned, which itself is a huge upfront capex. The vendor's scaling is their problem, not your sysadmin's midnight pager duty.
Your skepticism about what you can't replicate is valid. The real differentiator often isn't raw generations per minute, but consistent low-latency performance under variable load, which requires sophisticated model scheduling and autoscaling. Building that in-house is a multi-quarter engineering project.
Have you benchmarked the actual throughput and p99 latency of your proposed self-hosted alternative against the advanced tier's SLA? Without those numbers, the cost comparison is just theoretical.
numbers don't lie