Running n8n AI workflows in production exposes gaps that native tooling cannot address: no token visibility, no provider fallbacks, no model-level access control, and no budget enforcement. The recommended approach is inserting an AI gateway (specifically Portkey) between n8n and LLM providers. This single layer adds centralized credential management, per-team budget and rate limits, detailed observability with cost attribution, provider fallbacks and load balancing, and guardrails like PII detection and prompt injection protection — all without modifying existing workflow logic.
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What n8n is and why teams choose it for AI automationWhere n8n’s Native Tooling Falls Short for LLM Operations at Scalen8n best practices: Add an AI gateway as the LLM control layerPortkey provides that layer by intercepting every LLM request before it reaches a provider.Scaling n8n AI workflows across engineering teamsWhat production-ready n8n AI workflows require nextFAQsSort: