Yes, but differently. n8n has a visual AI agent builder with LangChain integration, 12 vector store integrations, MCP client and server nodes, and an evaluation node for testing agent outputs — great for prototyping chatbots and agent chains. Kestra orchestrates AI workloads the same way it orchestrates everything else: as steps in declarative pipelines with full state tracking, retries, and scheduling — built visually in the UI or in code. You can call any model API, run any ML framework, and package any environment in a Docker container. A single Kestra flow can handle data extraction, model training, evaluation, deployment, and monitoring as one end-to-end pipeline. If you need a visual agent builder, n8n excels. If you need production AI pipelines integrated with data and infrastructure workflows, Kestra is built for that.