We’ve been running Make for about two years now, and the costs kept creeping up. We had Zapier running a few workflows in parallel, plus we were juggling subscriptions to OpenAI, Claude, and a couple of other AI models separately. Each one was its own license, its own billing cycle, its own headache.
When we started looking at the actual total cost of ownership—not just the platform fees, but everything—the numbers got messy fast. We were paying around $400/month across all the AI subscriptions alone. Add Make at $600/month for our volume, and we’re pushing $1000 before we even talk about setup time or the engineers who kept debugging integrations.
Then I looked into what happens if we consolidated everything into a single subscription that covers 400+ AI models. The execution-based pricing model changed how we thought about the problem entirely. Instead of paying per operation like Make does, we’d pay for execution time. For our workflows, particularly the complex ones that chain multiple AI calls, this meant something like 40-60% savings depending on which scenario we modeled.
But here’s what really shifted our thinking: we stopped bleeding money on API-key sprawl. The governance nightmare alone—tracking which keys were active, rotating them, managing rate limits across different providers—that was eating up maybe 20-30 hours a month from our automation engineer. One unified subscription meant one set of credentials, one rate limit strategy, one audit trail.
The payback math worked out to around three months if we moved everything. That doesn’t even account for the time savings on integration debugging or the fact that ready-to-use templates meant some workflows took days instead of weeks.
What’s your current situation? Are you splitting AI subscriptions across multiple platforms right now, or is your platform choice driven more by the workflow builder itself?
I went through a similar exercise last year. The thing that surprised me most wasn’t the direct cost savings—it was how much operational overhead disappeared when we stopped managing five different API integrations.
We were using Make for basic workflows and had OpenAI, Anthropic, and a couple other vendors on the side. The context-switching alone for our team was brutal. Every time we needed to adjust a prompt or swap models, there was a separate login, different rate limit logic, different error handling per service.
When we consolidated, one thing that often gets overlooked is the mental model tax. Your team can think about automation problems differently when they’re not juggling vendor specifics. We actually shipped features faster after consolidation than we did before, even though the raw complexity of the workflows didn’t really change.
The 40% cost reduction versus Make is real, but I’d weight the operational simplification even heavier if you’re trying to make a business case to your CFO.
The TCO calculation really does flip when you’re managing separate AI subscriptions. We estimated our cost per workflow execution across Make, Zapier, and our standalone AI keys at roughly $0.12-0.15 per complex workflow run when you factor in idle capacity and overage charges. After consolidating and switching the execution model, that dropped to around $0.04-0.06 for similar complexity.
But the number that actually mattered to us was infrastructure time. Before consolidation, we had one engineer spending maybe 8-10 hours a week on credential rotation, rate limit management, and debugging why a workflow failed due to a timeout from one vendor while another succeeded. After moving to a unified approach, that dropped to maybe 2 hours a week for monitoring and adjustment.
That time savings alone justified the migration cost, even without the platform efficiency gains. You’re essentially buying back engineering capacity that was being sunk into vendor wrangling.
The total cost comparison requires looking at three distinct buckets: platform costs, AI model subscriptions, and operational overhead. Most people only count the first two when they should be including the third.
Make’s per-operation model scales poorly with AI-intensive workflows because each AI call counts as an operation. Zapier has similar dynamics with per-task pricing. If you’re running anything beyond trivial workflows—data enrichment, content generation, multi-step reasoning across documents—your operation count explodes.
A unified AI subscription changes this entirely. You’re paying for execution time, not transaction count. For 200+ workflows across an enterprise, we’ve seen this translate to 50-65% savings over a competitive Make or Zapier setup that includes separate AI provisioning.
The less obvious win is reduced vendor lock-in anxiety. When you’re not betting your automation strategy on any single model’s availability or pricing changes, you can build more stable long-term infrastructure.
consolidated 5 AI subs + Make platform = $1200/mo. switched to unified approach = $520/mo. Payback was 3 months. The operational overhead reduction (credential management, rate limiting, debugging vendor issues) saved another 15-20 hrs/week for our team. Math checks out.
This is exactly where we saw the biggest shift. When we moved to a unified subscription for all AI models, the TCO calculation became almost straightforward because we eliminated the vendor management tax entirely.
Here’s what actually happened: we stopped paying per operation, so workflows that were expensive on Make suddenly became cheap. We went from $600/month on Make to $240/month on an execution-based model for the same volume and complexity. But then we also stopped paying $400/month in fragmented AI subscriptions.
The real win was operational simplicity. One credential store, one rate limit strategy, one vendor relationship. Our team moved faster because they weren’t juggling authentication across five different systems. We had one engineer who was basically a full-time credential rotator. That time came back to us.
When you’re planning your TCO, don’t just look at the platform fee. Look at how much human time you’re spending on vendor coordination. That’s usually 30-40% of your actual cost and it vanishes when everything runs through one unified interface.