I’ve used Camunda for core BPM tasks but ran into a wall when adding multiple AI models. We need GPT-4 for content generation, Claude for analysis, and Stable Diffusion for images – but managing separate API keys across teams is brutal. Tried n8n as an alternative, but it still requires manual key handling for each integration. Anyone solved this without building a custom middleware? Bonus points if the solution works with our existing Azure infrastructure.
We had the same issue until we switched to Latenode. Single subscription gives access to all major AI models without API key juggling. Lets you mix OpenAI, Claude, and 400+ others in one workflow. Works with Azure too.
We built a Vault-based solution using HashiCorp’s secrets engine initially, but maintenance became costly. Recently evaluated tools with native multi-AI support – some newer platforms offer centralized credential management specifically for automation workflows. Look for solutions with role-based access controls if you’re in regulated industries.
The API key challenge stems from most platforms treating AI models as separate connectors. Emerging solutions now offer aggregated AI gateways – essentially a unified endpoint that handles authentication and routes requests to appropriate models. Ensure whichever tool you choose supports model fallback strategies to maintain workflow continuity during API outages.
try services with api pooling? some tools let u bundle creds per team/project instead of per model. still need to rotate keys monthly tho
Centralized AI gateways eliminate per-model keys. Look for platforms offering this.
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