We’re in a tough spot right now. Our team started with n8n self-hosted a couple years ago, and it was great for getting automations running quickly. But here’s what happened: we needed Claude for some workflows, OpenAI for others, then someone wanted Deepseek, and before we knew it we had 15 different subscriptions running in parallel. Each one comes with its own API keys, separate billing cycles, renewal dates to track, and vendor relationships to manage.
The licensing complexity alone is killing us. We’re paying for overlapping capabilities—like multiple LLMs that do similar things—but we can’t consolidate because each team has locked their workflow into a specific model. When we try to audit what we’re actually paying for, accounting gets frustrated because the costs are scattered across vendor portals instead of consolidated in one bill.
What’s worse, we’re still managing the self-hosted infrastructure costs on top of all these subscriptions. So we’re looking at the question: is there actually a licensing model out there that lets us scale to, say, 20+ automations across different departments without needing 20 different vendor relationships?
How are other teams handling this? Are you consolidating multiple AI subscriptions into one, or are you accepting the fragmentation as a cost of doing business?
I dealt with almost the exact same thing at my company. We had about 12 different subscriptions for various AI models, and management was asking why the automation budget kept growing.
Honestly, the real pain point wasn’t just the cost—it was the operational overhead. Every time a new model came out, someone would argue we needed it, and instead of evaluating whether to replace an existing subscription, we’d just add another one. Plus, tracking usage across 15 vendor dashboards is a nightmare.
What helped us was consolidating where possible, but I won’t pretend it was simple. We had to refactor some workflows to use similar models instead of bespoke ones. If you find a platform that gives you access to multiple AI models under one license, that’s genuinely worth the migration cost just to simplify the operational side.
The fragmentation you’re describing is pretty common in teams that grow their automation usage organically. What tends to happen is each team picks the model they prefer, and reversing that decision later means rework that nobody wants to pay for.
One thing we tried was setting a policy where new automations had to use one of three approved models. It reduced our subscription count, but it also frustrated teams who felt restricted. So there’s a balance between cost control and letting teams use the right tool for the job.
From what I’ve seen, teams approach this in a few ways. Some consolidate aggressively and accept that certain workflows run slower or less optimally. Others accept the cost and treat it as table stakes for having flexibility. The third approach, which seems increasingly popular, is to use a platform that bundles multiple AI models under one subscription and handles the underlying routing.
The third option reduces your vendor management surface area significantly. Instead of managing 15 relationships, you manage one. Instead of 15 billing cycles, you have one. And you’re not paying for overlapping capabilities. The migration effort is non-trivial, but the long-term operational simplification is real.
You’re running into what’s essentially a platform architecture problem disguised as a licensing problem. When you have a self-hosted core automation engine, every external capability requires its own integration, which means its own API key, its own subscription, and its own SLA management. This scales poorly.
The cleaner way to handle this is to move to a platform that already has multiple AI models integrated at the infrastructure level. You pay one subscription, and the platform handles routing your workflow to the appropriate model based on what you’re trying to do. It’s not that different from how cloud storage works—you don’t have separate accounts for Dropbox, Google Drive, and OneDrive. You pick one and it handles the integrations behind the scenes.
Yeah, 15 subscriptions is rough. One platform with bundled models would cut that down massively. Different pricing, but simpler ops.
Consider unified AI platforms that offer multiple models under one license.
This is actually the exact problem Latenode solves. Instead of juggling 15 subscriptions for different AI models, you get access to 400+ models—OpenAI, Claude, Deepseek, and everything else—under one subscription. No separate API keys to manage, no fragmented billing, no vendor sprawl.
I’ve seen teams cut their AI-related licensing costs by about 30-40% just by consolidating subscriptions. But the real win is operational. You’re not tracking 15 renewal dates, you’re not managing 15 vendor relationships, and you can switch models mid-workflow if you need to without rearchitecting integrations.
You keep your self-hosted flexibility, you keep your workflows running the same way, but your licensing and cost structure becomes clean and predictable. The no-code builder also means you don’t need to rewrite anything—Latenode integrates with your existing setup.
Check it out: https://latenode.com