đź’¬ Handle LinkedIn inbox RAG replies with Unipile, Claude, Pinecone, and Airtable
⚡ 992 views · 💬 Support Chatbots
💡 Pro Tip — If you’re pulling LinkedIn data through HTTP requests or dealing with API restrictions, there’s a community node called ScraperNode that handles this natively. It has dedicated scrapers for profiles, companies, jobs, and people search — you just pass a URL and get structured data back.
Description
Quick overview
Automatically ingest your knowledge base, monitor your LinkedIn company page inbox, and reply to leads and customers with AI-drafted, source-grounded answers. Classifies every message, checks for spam, drafts replies using Claude and Pinecone RAG, and lets you auto-send or review each reply in Airtable.
How it works
- A Google Drive trigger watches a folder for new or updated documents, downloading each file automatically as it’s added.
- Each document is split into chunks, embedded, and upserted into a Pinecone vector index, building a searchable company knowledge base.
- A webhook receives every new LinkedIn message sent to your company page via Unipile, filtering out messages you sent yourself.
- The last few messages in the conversation are fetched and formatted into a chronological transcript for context.
- An AI agent classifies the message’s intent (lead, support, partnership, recruiting, spam, or other) using shared conversation memory.
- A second AI agent drafts a reply, searching the Pinecone knowledge base for relevant facts before answering, and saves the draft to Airtable.
- Depending on a configurable auto-send toggle, the reply is sent immediately via Unipile, or held in Airtable until a human approves it — which triggers a third workflow to send it.
Setup
- Connect your Unipile account (LinkedIn company page messaging) and note your DSN/API host for the HTTP Request nodes.
- Connect Pinecone and create an index sized to match your embedding model’s output dimensions (this template uses Google Gemini embeddings).
- Connect Google Drive and choose the folder that holds your knowledge-base source documents.
- Connect Airtable and create a base with four tables — Drafts, Spam, KB Log, and Errors (see the sticky notes for exact field names).
- Connect an LLM provider for the classification and reply-generation agents (this template uses Claude via OpenRouter, but any tool-calling-capable model works).
- In Unipile’s dashboard, create a webhook (event: messaging) pointing at Workflow 2’s production URL. In Airtable, add a “Run a script” automation on the Drafts table (trigger: status = approved) that posts to Workflow 3’s webhook.
Requirements
- A Unipile account with a connected LinkedIn company page
- A Pinecone account and index
- A Google Drive account with a folder for source documents
- An Airtable account — note: a paid plan (Plus/Pro/Enterprise) is needed, since Workflow 3’s approval trigger relies on Airtable’s “Run a script” automation action
- An LLM provider credential for Claude (or another tool-calling-capable model) — this template uses OpenRouter
Customization
- Toggle the autoSend field on Workflow 2’s Config node to send replies automatically instead of requiring human approval in Airtable
- Swap the embedding model or Pinecone index freely, as long as ingestion and retrieval use the same model and dimensions
- Edit the system prompts on “Classify Message” and “Generate RAG Reply” to match your company’s tone, categories, or knowledge domains
Additional info
This is 3 separate workflows meant to run together: a knowledge-base ingestion pipeline, an inbox monitor + RAG reply bot, and a human-approval send workflow Free-tier LLM models may not reliably support tool-calling or structured JSON output — a paid model is recommended for production use
Contact: Email: salmanmehboob1947@gmail.com Linkedin: https://www.linkedin.com/in/salman-mehboob-pro/
đź”— Nodes Used
Airtable, HTTP Request, Webhook, Google Drive, Google Drive Trigger, AI Agent
đź“Ą Import
Download workflow.json and import into n8n:
Workflow menu → Import from File