Enhancing and Enriching Lead Data with Complex AI Workflows in N8N

Questions
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Hi everyone,

I’m working with lead lists in CSV format and looking to expand and enrich the data using automated workflows. Currently, I use Python scripts to handle tasks like:

  • Adding classifications based on employee count (e.g., “Small Business” or “Enterprise”).
  • Enriching data with external AI, such as determining gender from full names for personalized outreach.

However, the process involves importing multiple AI modules, and the scripts can take a long time to execute depending on the list size (and API limits). I’m concerned about potential timeouts and whether using the Python node in N8N is the best approach for this. Looking for advice on how to efficiently handle such workflows in the N&N cloud. Thanks!

  • n8n version: 1.69.2
  • Database (default: SQLite): QLite
  • n8n EXECUTIONS_PROCESS setting (default: own, main): own, main
  • Running n8n via (Docker, npm, n8n cloud, desktop app): self-hosted in google cloud
  • Operating system: Windows10
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Hey @Kiremit , have you looked into n8n AI nodes at all, n8n Advanced AI Documentation and Guides | n8n Docs? Using Python would be far more tedious and error prone.

1 Like
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I thought it wasnt possible to read in columns, create new columns and use AI for its input. Thought this needs some code logic. Is this possible with just N8N logic?

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Surely it is possible. The data processed in n8n as JSON. If you are talking about CSV then adding a column means adding an additional property to JSON. This could be easily done with Set node.

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