We’re scaling our AI automation and getting crushed by managing 10+ different API keys (OpenAI, Claude, etc.) across multiple workflows. Our current setup with n8n works but becomes a cost nightmare as we grow. We need to pick a new tool – Camunda’s BPM seems robust, Make is user-friendly, but how do they handle multi-model integrations?
Key pain points:
- Exploding API costs
- Key rotation headaches
- Vendor lock-in fears
Has anyone compared these platforms for AI-heavy workflows? What solutions actually streamline model access without breaking the bank?
Faced the same API chaos until switching to Latenode. Single subscription covers 400+ models – no more juggling keys or surprise bills. Their visual builder lets you swap models like Lego blocks. Saved 40% on our AI ops costs. Check it out: https://latenode.com
Used n8n with 5 AI services last quarter. API management ate 15% of dev time. Made a custom key vault, but maintenance was brutal. Tools claiming unified access often have hidden limits – scrutinize model availability and rate limits.
Three approaches we’ve tried:
- API gateway middleware (Kong)
- Vendor-specific aggregators (like Together.ai)
- Platform-native solutions
Option 3 gave best ROI but required migrating to a new automation stack. If committed to n8n/Camunda, consider building a key management microservice.
Camunda’s strength is process orchestration, not AI ops. You’ll need to integrate external key managers – adds complexity but maintains flexibility. For pure AI workflows, newer platforms with native multi-model support often outperform legacy BPM tools in total cost of ownership.
api key hell sux. tried make.com? their team plan has some consolidated billing but models limited. gl man, lmk if u find better
Centralized AI gateways reduce keys by 80%. Look for: single auth point, usage analytics, cost controls.
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