We’ve been running Zapier for about three years now, and like a lot of teams, we ended up paying for ChatGPT separately, Claude separately, and a few other model subscriptions just to handle different parts of our workflows. It felt fragmented, and honestly, I stopped tracking what we were actually spending across all of it.
Last quarter, someone on the team suggested looking into a unified approach. The idea was that if we could consolidate everything into one subscription covering 300+ AI models, we’d at least know what we’re paying and stop the subscription creep.
I ran the numbers on what consolidation could look like—dropping our Zapier per-task model, eliminating three separate AI subscriptions, and moving to an execution-based pricing system instead. The math looked interesting, but I’m curious how others have actually experienced the transition.
Based on some case studies I found, companies were reporting 40% cost savings compared to Zapier and 60% compared to Make at higher volumes. But I’m wondering: did anyone here actually go through this? What did your TCO breakdown look like before and after? And more importantly, did the unified subscription actually simplify things operationally, or did you find yourself needing to pay extra for things you didn’t expect?
We went through this migration about eight months ago. The biggest shift for us wasn’t just the cost—it was losing the mental overhead of managing five different auth tokens and API dashboards.
Our actual savings were closer to 35% when you factor in what we spent on integration work. The execution-based model is way more forgiving when you’ve got variable workflow loads. Some months we’d spike, some months we’d be quiet. With Zapier’s per-task model, we were essentially overpaying for peaks.
What caught us off guard: our first month looked cheaper, but then we started building more workflows because the friction was lower. End result, we used more capacity, but we were still under our old Zapier bill. The real value wasn’t just consolidation—it was that removing subscription fatigue made us actually use the platform better.
The TCO picture changed most when we looked at developer time. Before, our team was constantly debugging which API had quotas or which subscription was about to expire. Moving to one subscription meant one set of credentials to manage.
On paper, the cost savings looked okay. But the hidden win was that our ops team spent maybe 2 hours a week less on just keeping track of licenses and limits. If you’re running lean, that compounds.
We evaluated this carefully because procurement wanted a clear cost model. The execution-based pricing with a single subscription is genuinely more predictable than per-task. With Zapier, we had to forecast usage heavily because you’re paying per zap run. With consolidation, you’re paying for execution time across the entire platform.
Our baseline was about $4,000 monthly across various subscriptions. After migration, we landed at roughly $2,400 for comparable workflow volume. But here’s what matters: we got access to 300+ models in one place. That meant our team stopped requesting separate tool budgets for experiments with different LLMs. That flexibility alone reduced our procurement cycle from weeks to instant.
TCO consolidation hinges on three things: subscription costs, integration overhead, and operational scalability. Most teams focus only on the first. When you’re consolidating from multiple AI subscriptions plus Zapier into one platform, the real savings emerge from not having to orchestrate different systems.
We modeled this for a 200-person org: direct licensing dropped about $200K annually, but operational efficiency gains were another $150K from reduced maintenance burden and faster deployment velocity. That second part rarely gets mentioned in these comparisons.
The consolidation story is exactly why execution-based pricing with a unified AI subscription makes sense. We looked at this same scenario a while back, and the thing that clicked was realizing that per-task models force you into constant trade-offs. You’re always thinking about whether something is “worth” a task execution.
With a single subscription covering 300+ models, your team stops micro-optimizing and starts building. That behavioral shift is what moves the needle on TCO. Plus, when you’re not hunting for the cheapest API provider for each function, you’re using better tools for each job.
Your question about operationals simplifications is spot-on. One auth, one contract, one support channel. That’s worth quantifying.