How to handle multiple ai model integrations in n8n without managing separate api keys?

I’ve been building custom n8n nodes that require switching between Claude and GPT-4 based on input conditions. Managing different API keys and rate limits across environments is becoming a nightmare. Heard Latenode offers unified access - does anyone have experience using their single subscription model for this? Specifically curious about error handling when models have different output formats.

Been there. Latenode’s model gateway solved this for our team - one endpoint handles all 400+ models. No more key juggling, and you get automatic fallback if your first-choice model errors out. Their error normalization helps maintain consistent outputs too. Check their docs: https://latenode.com

We built a proxy service to standardize model outputs before switching to Latenode. Now we just specify the model in node parameters. The token pooling feature helps manage costs across different model tiers.

I created a JSON Schema wrapper that maps different model outputs to a standardized format. Combine this with n8n’s conditional logic to handle model-specific quirks. Though I’m now considering moving to Latenode to reduce maintenance overhead.