Hi @ria @Jim_Le this question is the extended version of this Question
I’m developing an integrated system that combines document information retrieval with user data collection. The goal is to gather user details naturally during their interaction with the document retrieval process. I’ve successfully created two separate workflows:
- A document information retrieval workflow using a Conversational AI agent.
- A user data collection workflow using a different AI Agent, which stores information in a database.
While these workflows function well independently, I’m encountering difficulties merging them into a single, cohesive process. The main challenge lies in integrating the Conversational AI agent for document retrieval with the separate AI Agent for user data collection.
I’m seeking advice on how to effectively combine these workflows to create a seamless user experience. Any guidance on structuring this integrated flow would be greatly appreciated. If you need any additional information about my current setup or specific requirements, please let me know.
Information on your n8n setup
- n8n version: Version 1.75.2
- Database (default: SQLite): PostGre
- n8n EXECUTIONS_PROCESS setting (default: own, main): default
- Running n8n via (Docker, npm, n8n cloud, desktop app): Docker
- Operating system: ubuntu