We went through a serious evaluation last year when our team realized we were paying for OpenAI, Anthropic, Google’s models, and a few others separately. Each one had its own contract, its own billing cycle, and honestly, nobody really knew what we were spending overall.
When we started looking at Make vs Zapier for enterprise automation, the picture got even messier. We’d be comparing pricing on one platform, then realize we needed to factor in the cost of maintaining all these model subscriptions on top of it. The math just wasn’t adding up cleanly.
Then we did the calculation differently. We looked at what happens if you consolidate access to 300+ models through a single subscription. Suddenly, you’re not paying for overlap anymore. You’re not maintaining separate API keys. You’re not managing five different vendor relationships for essentially the same thing.
The spreadsheet I built showed that the per-execution cost was significantly lower when you stop thinking about “which model subscription do we need” and start thinking about “which model is right for this specific task within one unified pricing structure.”
I’m curious how others are actually handling this on their side. Are you still managing separate subscriptions for different models, or have you found a way to consolidate? And when you’re comparing platforms like Make or Zapier, how are you factoring the AI model licensing piece into your ROI calculations?
We had the exact same problem. We were juggling OpenAI’s subscription, then Claude, then we added Gemini later. Each one felt like it made sense at the time, but the administrative overhead was brutal.
What actually helped us was stopping the piecemeal approach. Instead of asking “which platform should we use?”, we asked “what are all the tasks we need to automate, and which models are best for each?”
Once we did that, it became clear that having everything under one subscription made more sense. We didn’t have to worry about hitting rate limits on one service and then scrambling to switch models. The cost per execution dropped because we weren’t paying for unused capacity across five different plans.
The TCO calculation became so much simpler. We could actually compare Make vs Zapier without that weird shadow cost of all the AI subscriptions muddying the water.
I went through a similar consolidation process about eight months ago. The key insight I had was that most teams don’t actually need all the specialized models they’re paying for. We were maintaining subscriptions for models we used maybe twice a month.
When we modeled the ROI of switching to a unified approach, the payback period shrunk significantly. We calculated that we were essentially throwing away about 30-40% of our AI budget on unused capacity. By consolidating into one subscription that gave us access to everything, we could be more opportunistic about which models we used for which tasks.
The enterprise pricing for Make and Zapier started looking way different once that shadow cost disappeared from the equation. Our team could actually have an honest conversation about which platform to choose based on automation capabilities, not just “which one doesn’t add another $5k a month to our opex?”
The consolidation math is straightforward once you have the data. Most organizations paying for multiple AI subscriptions are essentially paying for the same foundational capabilities multiple times. The real cost driver isn’t the models themselves—it’s the overhead of managing separate vendor relationships and the waste from unused capacity.
When evaluating enterprise platforms, factoring unified AI access changes the comparison significantly. You can now measure cost per task execution more accurately because you’re not allocating a portion of five separate subscriptions to each workflow. The platform’s own pricing becomes the primary variable, not a secondary concern buried under licensing complexity.
The teams I’ve worked with saw 40-60% TCO reduction after consolidation, depending on their initial usage patterns. That’s a substantial number when you’re making an enterprise platform decision.
we cut our model spending by 55% after consolidating. the make vs zapier choice became way clearer once we weren’t carrying duplicate subscriptions. execution-based pricing made the math honest.
This is exactly the problem we see organizations run into constantly. You’re spending money on multiple AI model subscriptions when you really just need access to the right model for each task.
What changes everything is having one unified subscription that covers 400+ models. You stop managing API keys across vendors. You stop paying for overlap. You stop wasting cycles on vendor management.
When we helped a team model their TCO for enterprise automation, they realized their actual cost per execution dropped by nearly half once they weren’t carrying all those separate licenses. The Make vs Zapier decision became straightforward because the competing platforms’ pricing was now the only variable, not buried under AI licensing complexity.
You get consistency across your entire automation stack. One pricing model. One vendor relationship. Access to every major model without negotiating separate contracts.
If you want to see how this actually works in practice and model it for your own workflows, start here: https://latenode.com