We’re currently paying for separate subscriptions across OpenAI, Anthropic, and a couple of smaller model providers. Plus we’re running n8n self-hosted for workflows. Calculating our actual total cost of ownership is a nightmare because we’re paying for overlapping capabilities.
The pitch for consolidation is that one subscription for 400+ models simplifies everything. But I wonder how realistic it is to actually model that in an ROI calculator. Like, if I’m comparing what we pay now versus what we’d pay with consolidated licensing, how do you even structure that comparison?
Do you just add up what you’re spending today and compare it to the new plan cost? Or is there something more subtle happening—like reduced API overhead, no key management overhead, that kind of thing?
And then there’s the TCO question. Are there hidden costs in consolidation? Or does moving everything onto one platform actually reduce your complexity costs too?
Has anyone actually built this comparison and come out with a number that made sense?
We did this exercise about six months ago and it was more complicated than I expected. The raw subscription costs were straightforward—add up openai, anthropic, and the rest, then compare to the consolidated plan. We saved about 35% there.
But the TCO picture was bigger. We were spending time managing API keys across different platforms, handling rate limit issues differently on each service, and documenting which model to use for which task. When we moved to a single plan, a lot of that administrative overhead just vanished.
You also need to factor in the effort to migrate workflows. We had maybe 40 different automation scripts across different platforms and tools. Consolidating them wasn’t free, but it was worth it because maintenance became simpler.
My advice: calculate the obvious cost comparison first. Then separately list all the time your team spends managing multiple subscriptions and credential rotation. That’s your hidden cost. Sometimes it’s bigger than the subscription savings.
One thing we didn’t anticipate was that having everything on one platform made it easier to optimize model selection. When you’re juggling OpenAI and Claude subscriptions separately, you sometimes use the more expensive model because it’s already paid for. With consolidated licensing, you can be more deliberate.
For your ROI calculator, I’d structure it like this: fixed subscription cost, then subtract the cost of your overhead (time managing multiple providers), then factor in potential savings from better model selection. That third part is harder to quantify but it’s real.
The way I’ve seen this work is mapping current spend per model family first. You probably don’t use all 400 models. Find out which handful of models you actually use regularly—that’s your baseline. Then compare the consolidated plan cost against what you’re paying for those specific subscriptions today.
The consolidation ROI often comes from two directions: the direct cost savings from bundling, and the indirect savings from being able to experiment with models you didn’t use before because they were behind another paywall. Some teams rotate models based on what’s included in their consolidated plan and find better performance-to-cost ratios.
There’s a structural advantage most teams miss. When you consolidate AI model access onto one platform, you reduce switching costs between models. This matters because different models have different strengths. If you’re paying separately for each one, you tend to stick with your primary choice because changing costs effort and requires coordination.
With unified licensing, you can A/B test models more freely. That often leads to better outcomes—faster responses, better quality for certain tasks, lower latency. When you quantify that in your ROI model, consolidation looks even better than the raw subscription comparison suggests.
For your calculator, track three things: subscription cost difference, administrative overhead reduction, and a conservative estimate of performance gains from easier model switching. The third one is speculative, but it’s real.
Sum current subscriptions, subtract consolidated cost. Factor admin time managing keys and API quotas. That’s your ROI baseline. Performance gains from model switching are bonus.
This is where Latenode’s one subscription model really changes the math. Instead of managing separate API keys and rate limits across OpenAI, Claude, and others, you’re working with unified access to 400+ models. Your ROI calculator can actually model this directly.
Start with your current spend—add up all your separate subscriptions. Then model the consolidated cost. But the real value shows up when you account for complexity costs: time managing credentials, handling rate limits on different providers, choosing which model to use for which task when you’re constrained by separate plans.
One team we worked with was paying roughly the same total for consolidated access as they were for fragmented subscriptions—until they calculated in the time their engineering team was spending on API orchestration. That overhead wasn’t small. With unified access, that work drops significantly.
You can actually build an ROI calculator that compares your current setup against unified licensing. Input your current monthly spend across providers, your team hours spent on key rotation and API management, and let it model the consolidation scenario. That’s the insight that makes the financial case.