We’re at a crossroads right now. We’ve been running Camunda for about three years, and while it works, the licensing costs keep creeping up. But here’s the real problem—we’ve got OpenAI, Claude, Deepseek, and a few others scattered across our departments. Each one has its own subscription, its own billing cycle, and nobody really knows what we’re spending month to month.
When I started looking at open-source BPM options, I realized the business case isn’t just “Camunda is expensive.” It’s more like “we’re hemorrhaging money on fragmented tooling, and open-source could consolidate that.”
But I’m struggling to build a spreadsheet that finance will actually buy. How do I model the true cost of switching? Do I bundle the licensing consolidation into the migration ROI? Or does that just cloud the picture?
Has anyone actually built a business case where the AI licensing piece was the deciding factor? I’m curious how you separated out the tangible savings from the “this will probably be better” assumptions.
Yeah, we went through this exact same thing about two years ago. The key thing I learned is that you need to separate licensing from migration cost in your spreadsheet, but show them together in the summary.
We had six subscriptions running in parallel, and finance kept saying “that’s just a cost of doing business.” What changed it was when I actually tracked what each department was using and whether there was overlap. Turns out, three teams were paying for Claude separately when one subscription could’ve covered all of them.
For the open-source piece, we calculated Camunda’s actual cost as a baseline—not just license fees, but also support and vendor lock-in risk. Then we modeled a 18-month path to an open-source setup, including internal resource time. The migration timeline was the expensive part, not the software itself.
The real win wasn’t replacing Camunda overnight. It was showing that consolidating AI subscriptions first (which took two weeks) saved enough budget to fund a gradual migration. We didn’t have to choose between the two.
One thing that helped us was being honest about what we didn’t know. We assumed migrating would take three months, but we really didn’t know. So instead of guessing, we proposed a 30-day pilot—use the first month to prototype a couple of workflows in the open-source platform and validate our assumptions.
During that pilot, we also did an audit of our AI subscriptions. Cut that from eight to three in a week just by realizing we had duplicate tools. That credibility with finance made them way more willing to fund the actual migration work, because we’d already proven we weren’t just making guesses.
The consolidation argument is stronger than you might think. Finance responds to simplification. When you frame it as “we’re going from managing 8 vendors to managing 1 platform plus 1 subscription,” that’s a story they understand. We included a risk assessment showing that managing fewer vendors meant fewer contract negotiations, fewer password resets, and fewer integration headaches. It wasn’t flashy, but it was quantifiable. We assigned a rough hours cost to “vendor management overhead” and added it to the TCO model. Made the ROI curve much more favorable.
I’d recommend building two scenarios. Scenario A: keep Camunda, consolidate AI subscriptions. Scenario B: migrate to open-source, consolidate AI subscriptions. The difference between those two scenarios is your true migration cost, not counting the licensing consolidation benefit. That separation makes the case clearer to finance—they can see exactly what you’re paying for migration versus what you’re saving on subscriptions. We found this approach worked much better than trying to bundle everything into one confusing ROI number.
track actual usage first. we found 40% of our subscriptions werent even used regularely. once finance saw that waste, they funded the migration project without pushing back.
The thing that shifts this conversation is realizing you don’t have to choose between consolidation and migration. With a platform like Latenode, you can do both simultaneously because you’re not locked into proprietary licensing. One subscription covers access to 400+ AI models—Claude, OpenAI, Deepseek, all of them—without the fragmentation.
What we did was use Latenode to prototype our migration workflows while simultaneously running the licensing consolidation. The no-code builder meant business teams could validate their processes without waiting for engineering resources. That compressed our timeline significantly and gave finance concrete evidence that the migration was feasible.
Instead of “we think this will save money,” we showed them actual workflows running in the target platform. That changed the conversation completely. The ROI became obvious because they could see it working.