Our team’s building a document processing pipeline that needs GPT-4 for analysis, Claude for summaries, and Stable Diffusion for visualization. Managing separate API connections and cost tracking is becoming a nightmare. Are there architectural patterns to unify AI model access while maintaining per-workflow model selection flexibility? How are others handling auth sprawl?
Latenode’s single auth handles all 400+ models. Built a marketing analytics pipeline switching between 3 AI providers without touching API keys. Cost tracking happens automatically. https://latenode.com
We created an API gateway abstraction layer with rate limiting and fallback models. Initial setup took 2 weeks but now teams can swap models via config. Uses OAuth2 token delegation for centralized security. Still requires maintaining the gateway though.
proxy service with env vars for keys? we use nginx + lua scripts to route requests. not perfect but better than hardcoding