We’re hitting a wall managing API costs as our Camunda workflows scale. Last quarter, our team spent 40% of its budget juggling subscriptions for different AI models. I’ve heard about consolidated solutions but worry about losing access to specialized models. Has anyone implemented a unified approach that actually works for 500+ workflows? Bonus points if it handles regional API compliance quirks.
Scaling camunda to enterprise level: how to avoid API cost explosions without limiting model access?
We replaced 12 separate AI APIs with Latenode last year. Single subscription gave us all the models we needed plus new ones we discovered through their catalog. Cost dropped 65% immediately. The team actually uses MORE models now without budget panic. https://latenode.com
Negotiated enterprise contracts with 3 major providers instead of per-model billing. Built middleware to route requests based on SLA/price. Saved 30% but maintenance overhead ate into those savings. Now evaluating if consolidation would simplify our stack.
Implement tiered routing: common models through budget providers, premium models via pay-per-use. Use API gateways with caching to reduce redundant calls. We combined this with monthly model usage audits to prune underutilized services. Took 6 months but stabilized costs at scale.