This workflow is for professionals and teams who want to automate LinkedIn message replies with intelligent, human-like responses — without losing control over tone or accuracy. Ideal for founders, sales teams, DevRel, or community managers handling high-volume inbound messages.
Responding to every LinkedIn message manually is slow and inconsistent. Basic AI bots generate replies without context or nuance. This subworkflow solves both problems by using structured message routing from Notion and profile insights from UniPile to craft smart, context-aware responses.
This workflow takes the sender’s message and profile (from LinkedIn Auto Message Router with Request Detection) and references your centralized Notion database of message types. It uses that to either match the message to a known response or generate a new one using OpenAI's GPT model — all while following professional tone guidelines.
This is the third workflow in a 3-part automation system:
If a message comes from someone with low reach (e.g., under 1,000 followers), the AI politely deflects a meeting request. If an influencer reaches out, the AI immediately offers a booking link. Your team controls this logic by updating the Notion database — no edits to the workflow required.
Connect this workflow as a subworkflow in your router or Slack approval flow
Store your Notion API key and database ID in n8n
Provide the following parent inputs:
message
– The LinkedIn message textsender
– Name of the senderchatid
– Session ID (optional for memory)linkedinprofile
– Enriched array with LinkedIn context (follower count, connection info, etc.)Add your preferred AI model credentials (supports OpenAI, Gemini, or Ollama)
Optional: Customize system prompt to better match your brand voice