Automated Amazon Data Extraction and Fine-tuning AI Model

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This n8n workflow automates the process of scraping product data from Amazon, generating training data for AI, and fine-tuning a custom OpenAI model for marketing and product descriptions. The workflow begins with a manual trigger, allowing the user to initiate the process on demand. It then uses Bright Data’s web scraper to gather detailed product URLs from Amazon. Next, a custom code node processes this data, creating a JSONL formatted file with product descriptions suitable for AI training. This file is uploaded to OpenAI, where a fine-tuning job is automatically initiated to enhance the model’s capabilities. Finally, the workflow includes a chat trigger and an AI agent that leverages the learned model to generate marketing content or product descriptions dynamically, enabling efficient and scalable content creation for eCommerce or marketing teams. This setup is ideal for businesses looking to automate data collection and enhance AI-driven marketing strategies.

Node Count

6 – 10 Nodes

Nodes Used

@brightdata/n8n-nodes-brightdata.brightData, @n8n/n8n-nodes-langchain.agent, @n8n/n8n-nodes-langchain.chatTrigger, @n8n/n8n-nodes-langchain.lmChatOpenAi, @n8n/n8n-nodes-langchain.openAi, code, httpRequest, manualTrigger, stickyNote

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