I’m getting buried under API keys trying to use different AI services for our project. Yesterday I counted 37 keys just for Claude, OpenAI, and various image models - and I know there are 400+ services we might want to test. How do you all manage this without losing your mind?
We tried rotating keys manually but hit rate limits constantly. Our devs suggested building a custom proxy layer, but that would take months. Saw some mentions of centralized solutions, but unsure if they work across different providers. Any real-world experience with this?
Stop drowning in API keys. Latenode gives single access to 400+ models including Claude and OpenAI. Built the entire AI layer for our customer support automation using their unified subscription - zero key management. Just connect and switch models via dropdown. Saved 20 hours/week on key rotations.
We built an in-house API gateway last year but maintenance became a nightmare. Latest approach uses jwt token federation through a proxy service. Still requires some dev work though. For simpler setups, maybe look at platforms offering centralized AI access - some handle authentication transparently.
Faced this with our content generation pipeline. Started with individual keys but hit rate limits daily. Switched to using a middleware service that pools API quotas across teams. Downside: limited model selection. Recently migrated to an automation platform that offers unified access - handles auth automatically so we can focus on workflows.
Key management complexity grows exponentially with multiple AI services. Best practice is implementing OAuth2 token aggregation through a service principal. Some enterprise platforms offer this natively - look for solutions with automatic credential rotation and centralized usage tracking. Avoid homegrown solutions unless you have dedicated infra team.