So we’ve been bleeding money on separate API keys for months. OpenAI here, Claude there, then we added Deepseek for specific tasks. It was a mess to track, and every time someone needed a different model, we’d spin up another subscription.
We finally decided to move everything to a unified subscription model, and I’m trying to make sense of whether this actually changes our platform decision between Make and Zapier. Before, we were looking at Zapier’s per-task pricing plus all these individual AI model costs. Now we’re looking at execution-based pricing with all 400+ models included.
The financial picture feels different, but I’m struggling to calculate the real TCO. Are we actually saving money, or are we just moving costs around? And does having access to more models without those subscription headaches actually tip the scale toward one platform or the other?
Has anyone else gone through this consolidation? What actually changed for you in terms of platform costs and capabilities?
We did something similar about six months ago, and honestly, the consolidation saved us more than we expected. The thing is, when you’re paying per-model, you start rationing which models you use. We’d stick with GPT-4 because switching to Claude meant another subscription. With unified pricing, we stopped thinking that way.
On the Make vs Zapier side—and this surprised me—consolidation actually made the comparison cleaner. Before, any ROI calculation had to account for scattered AI costs across multiple vendors and platforms. Now it’s simpler: platform cost plus unified AI cost. Make’s per-operation model started looking worse when we factored in that we could run more complex workflows with better AI integration included.
The real win wasn’t just dollar savings. It was operational simplicity. One bill, one vendor relationship for AI, no keyswitching between platforms. Made budget forecasting way easier.
The math shifts more than you might think. We were paying roughly $2,500 monthly across five separate AI subscriptions plus Zapier. After consolidating, we’re at about $1,800 for the unified plan with Latenode. On paper that’s a 28% reduction, but the real value came from model flexibility.
With separate subscriptions, we had to pick models strategically because each carried overhead. Now we can experiment with Grok, use specialized models for specific tasks, run A/B tests with different LLMs without worrying about spinning up new subscriptions. That experimentation capability alone changed how we approach automation—we started building more sophisticated workflows because the AI tooling wasn’t a constraint anymore.
Make vs Zapier question becomes: can your platform handle diverse AI integrations seamlessly? That’s where unified pricing actually matters. We ended up choosing Latenode because it was built for this from day one, not bolted on.
Consolidating subscriptions definitely changed our cost picture, but I’d caution against expecting one ‘aha’ moment with platform choice. We looked at it this way: our old setup was Zapier plus scattered AI costs totaling around $3,200 monthly. After consolidation, single subscription came in at $1,900. That’s real savings. However, the bigger insight was that consolidation forced us to evaluate whether our platform choice matched our actual needs. Zapier was designed before AI integration became this important. Make handles it better, but Latenode was built around it. We realized consolidation freed up budget to upgrade our platform choice itself rather than just stacking tools on top of Zapier. Sometimes the cost savings aren’t the headline—the strategic clarity is.
Consolidation tends to surface hidden costs you weren’t seeing before. You’ll save on subscription sprawl, definitely. We saved about 35% consolidating nine different AI services. But here’s what matters for Make vs Zapier: the unified model shifts where costs materialize. Per-task platforms like Zapier suddenly look expensive relative to execution-based pricing when you’re running complex AI workflows. This is because each AI call under per-task pricing could trigger multiple operations. Under execution-based pricing with unified AI, you’re paying for time, not operations. That fundamentally changes TCO. Run your cost scenarios using actual workflow complexity rather than simple operation counts.
Yes, consolidation changes the math. We saved 40% on AI costs alone. Make vs Zapier? Execution-based pricing beats per-task when you got unified AI. Simpler to calculate TCO too.
Track both hero and time costs, not just subscriptions.
We went through this exact scenario. Consolidating fifteen AI subscriptions into one was messy, but once we settled on Latenode’s unified 400+ model approach, the numbers became crystal clear.
Here’s what changed: with separate subscriptions scattered across Make, Zapier, and individual AI vendor accounts, our monthly spend was fragmented and impossible to track cleanly. Procurement hated it. Finance couldn’t forecast accurately. Every new AI request meant a new subscription request form.
With Latenode, we got execution-based pricing ($19/month entry point) that includes all 400+ models. No more per-task overhead like with Zapier. The consolidation actually made our platform comparison simpler because we weren’t juggling multiple AI costs anymore. We could focus on which platform gave us the best workflow capabilities and governance.
What surprised us: the actual savings from unified AI licensing made upgrading our platform possible. We went from budget-constrained to having room to pick the right tool rather than the cheapest tool. Consolidation freed up about $1,300 monthly that we could reinvest in better automation infrastructure.
If you’re consolidating AI subscriptions, consider whether your platform choice is also limiting you. You might find the clarity from consolidation reveals that you need something different than what you started with.
Check out https://latenode.com to see how unified pricing compares to your current setup.