Extract & analyze brand content with Bright Data and Google Gemini
Needs changesNeeds changes. This template uses 1 thing(s) that n8n 3.0 removes: Function (legacy). 1 breaking item(s) found. Static check, last run 2026-10-19.
What this workflow does
This AI workflow has 18 nodes and runs manually, when you click “Execute workflow”. Along the way it connects Google Gemini Chat Model. It also calls api.brightdata.com and webhook.site over HTTP.
How it runs
Trigger: Manually, when you click “Execute workflow”.
- Set URL and Bright Data Zone (Edit Fields (Set)): sets 2 fields: url, zone
- Perform Bright Data Web Request (HTTP Request): calls api.brightdata.com (POST)
- Markdown to Textual Data Extractor (Basic LLM Chain): sends a prompt to an LLM, with model: Google Gemini Chat Model
- Summarize Content (Summarization Chain): summarizes text with AI, with model: Google Gemini Chat Model
- AI Sentiment Analyzer with the structured response (Information Extractor): extracts structured fields from text with AI, with model: Google Gemini Chat Model
- Initiate a Webhook Notification for Markdown to Textual Data Extraction (HTTP Request): calls webhook.site
- Create a binary data for textual data (Function): runs custom JavaScript (legacy Function node)
- Initiate a Webhook Notification for Summarization (HTTP Request): calls webhook.site
- Create a binary data for summary (Function): runs custom JavaScript (legacy Function node)
- Initiate a Webhook Notification for AI Sentiment Analyzer (HTTP Request): calls webhook.site
…plus 4 more steps. See the full node list below.
Services it uses
HTTP calls to: api.brightdata.com, webhook.site
Before you upgrade to n8n 3.0
1 thing in this workflow is removed in n8n 3.0. Fix it before you upgrade:
- Function (legacy) in Create a binary data for textual data, Create a binary data for sentiment analysis, Create a binary data for summary: replace with Code node, mode 'Run Once for All Items'.
| Removed in 3.0 | Replace with |
|---|---|
| Function (legacy) Create a binary data for textual data, Create a binary data for sentiment analysis, Create a binary data for summary | Code node, mode 'Run Once for All Items' |
Nodes used (9)
- Manual Trigger
n8n-nodes-base.manualTrigger - Basic LLM Chain
@n8n/n8n-nodes-langchain.chainLlm - Edit Fields (Set)
n8n-nodes-base.set - Information Extractor
@n8n/n8n-nodes-langchain.informationExtractor - HTTP Request
n8n-nodes-base.httpRequest - Google Gemini Chat Model
@n8n/n8n-nodes-langchain.lmChatGoogleGemini - Summarization Chain
@n8n/n8n-nodes-langchain.chainSummarization - Function
n8n-nodes-base.function - Read/Write Files from Disk
n8n-nodes-base.readWriteFile
From the author
Who this is for? The Brand Content Extract, Summarization & Sentiment Analysis workflow is designed for professionals and teams who need to monitor, understand, and act on public brand perception at scale. It is ideal for: 1. Brand Managers - Looking to track…