We’ve been running n8n self-hosted for about 18 months now, and I’ve watched our AI licensing costs spiral out of control. We started with just OpenAI, but then we added Claude for better document analysis, Gemini for image work, and a few specialized models for specific tasks. Now we’re managing 12 different subscriptions across teams, each with its own API keys, billing cycles, and vendor relationships.
The procurement nightmare alone is eating up hours every month. We have to track which teams are using what, manage expiring keys, handle vendor updates separately—it’s a mess. When I looked at our actual spend last quarter, we’re paying roughly $4,200/month across all these subscriptions, but I have no visibility into whether we’re actually using half of them.
I’ve heard people mention consolidating everything into a single subscription that covers multiple AI models, but I’m skeptical about whether that actually works in practice. Our workflows are pretty complex—we have autonomous processes pulling data from multiple sources and using different models for different stages. If we switched to something unified, would we lose flexibility? Would the transition cost us more in downtime than we’d save?
Also, I’m curious about the licensing side of things. With n8n self-hosted, we’re already paying a license fee. If we move to a platform with built-in AI access, how does that change our total cost of ownership? Are we just shifting the spend around?
Has anyone actually gone through a consolidation like this? What was the real migration effort, and did you actually see the cost savings you expected?
We went through this exact scenario about 8 months ago. We had 9 different AI subscriptions spread across our teams, and the API key management alone was a nightmare.
Here’s what actually happened when we consolidated: we moved to a unified platform that handles multiple models under one subscription. The transition itself took about three weeks of planning and testing, but the real savings came from the execution-based pricing model rather than per-task billing. We were essentially paying for operations on each platform, which compounds fast when you’re running high-volume workflows.
The flexibility concern is real, but I was surprised how much it didn’t matter in practice. Instead of worrying about which model to use, the platform’s selection logic handles it automatically based on the task. For complex workflows with multiple stages, it actually simplified things because we weren’t context-switching between vendor dashboards anymore.
Cost-wise, we went from $3,800/month to around $1,400/month. The biggest win wasn’t just the subscription cost—it was eliminating the overhead of managing keys, vendor relationships, and billing cycles. Our finance team went from three people doing administrative work on this to basically zero.
The migration itself wasn’t painless. We had to rebuild some workflows that were tightly coupled to specific model features, but that process actually made us realize how much technical debt we’d accumulated. Worth it though.
One thing I’d push back on is the assumption that you need all 12 subscriptions in the first place. Before you consolidate, I’d recommend doing an actual audit of usage. We found that three of our subscriptions were basically dormant—legacy stuff from old projects that never got cleaned up.
Once you trim the fat, consolidation becomes much simpler. And yeah, the unified pricing model does change your TCO calculation, but in a good way. Instead of thinking about per-API costs, you’re thinking about execution time. A workflow that takes 15 seconds costs you a few cents regardless of how many models it calls. That’s fundamentally different from paying per operation.
One warning though: not all unified platforms are created equal. When we were evaluating options, some still had limitations around model selection or response validation that meant we’d still need supplementary subscriptions. We ended up going with something that genuinely covered everything we needed.
The licensing side of n8n self-hosted doesn’t really change if you’re moving to a different platform entirely. You’re not layering costs on top of each other—you’re replacing the entire stack. So instead of your n8n license plus 12 AI subscriptions, you get a unified platform that handles both automation and AI access.
Which actually raises a good question: are you committed to staying self-hosted? That constraint matters because some of the consolidated options have specific deployment requirements. If self-hosting is non-negotiable for compliance reasons, that’ll narrow your options.