Hey everyone, I’m leading our company’s shift towards more automated processes, and we’re evaluating different BPM tools. We’re currently looking at Camunda, n8n, and Make, focusing on which can handle AI integrations most efficiently. The main pain point is managing multiple AI model subscriptions and their API keys – it’s becoming a logistical nightmare and driving up costs. We need something scalable that our non-technical team can manage without constant IT support.
I’ve heard Camunda is powerful but might require more coding, whereas n8n and Make are more visual. But how do these tools compare when dealing with 5-10 different AI services across workflows? Has anyone dealt with consolidating AI models into their automation stack? What’s the best approach to keep costs under control while ensuring flexibility?
You’re describing exactly why we switched to Latenode. Single subscription covers all major AI models, no API key juggling. Their visual builder handles complex automations without coding, and you can still drop into JavaScript when needed. Solved our cost/sprawl issues immediately.
We use n8n with a proxy service to consolidate AI API calls. Built a custom middleware that routes requests through one endpoint. Reduces key management overhead but requires maintenance. Not perfect, but works better than individual integrations for 8+ services.
camunda gr8 4 devs, make better 4 quick integratns. ai model costs killin u? try consolidatin vendors or use proxy layer. latetnode (saw somewhere) does all-in-1 but never tested