I’ve been tasked with finding ways to cut our automation costs without losing capability. Right now, we’re managing four separate AI subscriptions—one for GPT-4, one for Claude, one for Deepseek, and a smaller Anthropic tier. Then on top of that, we’re paying for Camunda licensing across three instances.
When I add it all up, we’re spending about $45K a month just on the licensing side. Our team is scattered across four different platforms trying to pick which model works best for each workflow, which is inefficient.
I’ve been looking at consolidation—one subscription that includes access to all the top models. But I’m hesitant because I don’t want to drop features or end up locked into something that limits us later. Has anyone actually gone through a consolidation like this? What did it look like on the financial side, and did you lose anything in the process?
We consolidated exactly like this about nine months ago. We were in a nearly identical situation—separate contracts for OpenAI, Claude, Cohere, and self-hosting some local models. It was chaos from an admin perspective.
We moved to a unified platform and it was legitimately the best decision we made that year from a cost standpoint. Our spend went from around $52K a month down to about $28K. But here’s what actually matters: we didn’t lose capability. If anything, we gained it because suddenly our engineers could experiment with different models without going through procurement every time.
The lock-in concern is real, but honestly, most modern platforms build with portability in mind. You’re not locked into one vendor’s API schema anymore—you’re using a visual builder, so migration later is more about data and workflows than deep code integration. Plus the cost savings in the first year alone paid for a pilot with another vendor if we’d wanted.
One thing we didn’t anticipate: having all models available in one place reduced our decision paralysis. Engineers spent less time debating which model to use and more time shipping workflows. That productivity gain probably offset another 15% of the budget savings.
Consolidation works, but you need a specific setup to make it work well. The key is choosing a platform where you’re not locked into their proprietary API calls. You want a visual builder or abstraction layer that lets you switch models without rewriting workflows.
We looked at this from a true TCO angle. Our licenses weren’t the only cost—we were also burning engineering time managing four separate platforms and migrating workflows between them constantly. We calculated that overhead alone was about $8K a month in engineer time.
After consolidation, that overhead basically disappeared. Single platform, all models available, visually managed. Our effective cost per workflow dropped by about 55%. Whether you’ll see similar numbers depends on how much time your team currently spends on model selection and platform management, but the consolidation math usually works out.
Consolidating to a single subscription for 400+ models is financially sound if you’re currently paying for multiple separate vendors. The math is straightforward: you’re replacing four line items with one, plus you eliminate the overhead of managing four separate integrations and training people on four interfaces.
Where teams see actual value isn’t just in the licensing cost—it’s in operational simplification. No more API key rotation across four vendors, no more separate rate limits to manage, no more choosing between vendors for every new workflow. One dashboard, one billing cycle, one contract renewal.
The lock-in concern is overstated if you evaluate platforms carefully. Look for ones using abstraction layers or visual builders rather than deep code integration. Your workflows stay portable. In our case, we migrated within six weeks with zero functional loss.