A 126-step web scraping & research automation, triggered by schedule, connecting HTTP / REST API, Google Gemini, Google Sheets, with built-in AI reasoning.
In plain terms: this gathers information from the web for you. It collects and organises data from Google Gemini, Google Sheets on a set schedule (e.g. daily) — competitor tracking, research, monitoring — and hands you the result.
126
Nodes
3
Integrations
119
Connections
Schedule
Trigger
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The real node graph exported from n8n — triggers (green), AI nodes (violet), services and logic — laid out as they run.
⚙️ How it works
Google Gemini Chat Model· lmChatGoogleGemini
Get row(s) in sheet in Google Sheets21· googleSheetsTool
Schedule Trigger· scheduleTrigger
Structured Output Parser· outputParserStructured
Google Gemini Chat Model1· lmChatGoogleGemini
Get row(s) in sheet in Google Sheets· googleSheetsTool
Schedule Trigger1· scheduleTrigger
Structured Output Parser1· outputParserStructured
Google Gemini Chat Model2· lmChatGoogleGemini
Get row(s) in sheet in Google Sheets22· googleSheetsTool
Schedule Trigger2· scheduleTrigger
Structured Output Parser2· outputParserStructured
Google Gemini Chat Model3· lmChatGoogleGemini
Get row(s) in sheet in Google Sheets1· googleSheetsTool
💼 Business analysis
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Business use case
An automated research/monitoring workflow that gathers external data (HTTP / REST API, Google Gemini, Google Sheets), structures it, and delivers insight on a schedule — competitor tracking, market monitoring, data collection.
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Market need
Timely external data (competitors, prices, trends) drives decisions, but collecting it by hand is impractical. Automated research is a durable need.
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Market value
Data/monitoring subscriptions run $50–$500/mo; the collection engine is the defensible core.