We’re currently managing five separate AI subscriptions (OpenAI, Anthropic, Google, one specialized model, and some older stuff we can’t retire yet). The licensing complexity alone is eating up time. Every time we need a new model or want to test something, it’s another approval cycle, another billing relationship, another API key to manage.
I’ve been trying to calculate what we’re actually paying across all of these versus consolidating into a single platform approach. The math is messy because of volume discounts, commitment periods, and the fact that some of these subscriptions are tied to specific products we can’t easily swap out.
What I’m realizing is that consolidation isn’t just about the line-item cost. It’s about overhead—one vendor relationship, one billing cycle, one set of rate limits to manage, one place where we can see total usage. But I’m also aware that moving to a unified model might mean paying for capacity we don’t use on some models while we’re overprovisioned on others.
Has anyone actually done this transition and mapped out where the real savings showed up? Was it just the per-model cost difference, or were there other factors that shifted your ROI calculation?