Scrape & summarize Product Hunt feedback with BrowserAct & Gemini AI
UnknownWhat this workflow does
This AI workflow has 10 nodes and runs manually, when you click “Execute workflow”. Along the way it connects Google Sheets, Google Gemini Chat Model, Slack and Browseract Workflows (community).
How it runs
Trigger: Manually, when you click “Execute workflow”.
- Get row(s) in sheet (Google Sheets): uses Google Sheets
- Loop Over Items (Loop Over Items (Split in Batches)): loops over the items in batches
- Send a message (Slack): uses Slack
- Run a workflow task (Browser Act): uses Browser Act
- Get details of a workflow task (Browser Act): get task
- AI Agent: runs an AI agent, with model: Gemini; output parser: Structured Output Parser
- Append row in sheet (Google Sheets): append
Services it uses
Before you upgrade to n8n 3.0
We can't fully verify this one: it relies on 1 community package, and n8n 3.0 turns unverified community packages off by default (N8N_UNVERIFIED_PACKAGES_ENABLED=false).
- Check that n8n-nodes-browseract-workflows is verified or supports 3.0 (used in Run a workflow task, Get details of a workflow task).
Nodes used (8)
- Manual Trigger
n8n-nodes-base.manualTrigger - Browser Act
n8n-nodes-browseract-workflows.browserAct - AI Agent
@n8n/n8n-nodes-langchain.agent - Structured Output Parser
@n8n/n8n-nodes-langchain.outputParserStructured - Google Sheets
n8n-nodes-base.googleSheets - Google Gemini Chat Model
@n8n/n8n-nodes-langchain.lmChatGoogleGemini - Slack
n8n-nodes-base.slack - Loop Over Items (Split in Batches)
n8n-nodes-base.splitInBatches
From the author
Product Hunt Launch Monitor - Scraping & Summarization of Product Hunt Feedbacks This n8n template provides automated competitive intelligence by scraping and summarizing Product Hunt launch feedback with a specialized AI analyst. This workflow is essential…