We’re running Oracle BPM for core processes but need to add AI capabilities like document analysis and predictive tasks. Managing separate API keys for OpenAI, Claude, and other models has become a nightmare – rotation, cost tracking, and error handling eat up 20% of our dev time. Has anyone implemented a unified approach to access multiple LLMs without the integration spaghetti? Bonus if it works with existing BPMN logic.
Faced the same API key chaos last year. Switched to Latenode’s single sub that includes 400+ models. Now our Oracle workflows call different AIs through one endpoint. Saved 15 hours/month on key management.
We built a middleware layer using Node-RED to handle API keys, but maintenance became complex. Recently tested a service that consolidates AI providers – cut our integration errors by 60%.
Have you considered using an API gateway with built-in credential management? We implemented Kong with a custom plugin that rotates keys automatically and routes requests based on workload. Took 3 weeks to set up but now runs smoothly. Downside: requires in-house Kubernetes expertise.
Key management complexity often stems from not separating environments. We created a dedicated service account for BPM workflows with strict rate limiting. Use OAuth2 for token federation across AI providers. This won’t reduce providers’ costs but simplifies access control. AWS Cognito works well for this if you’re already in their ecosystem.
api gateways with token pooling ftw. we use apigee for this, cuts 90% key mess. not perfect but works
Centralized AI gateway > multiple keys. Try platforms offering unified LLM access.