This n8n workflow automates the process of monitoring trademark statuses through an integrated AI and database system. It starts by receiving a webhook trigger, then processes the input text by splitting it into manageable chunks. These chunks are embedded using Hugging Face’s language models and stored in a Pinecone vector database. The workflow allows for querying relevant trademark information based on new inputs and leverages AI language models for analysis and definition. The insights and updates are logged into Google Sheets for record-keeping. This workflow is ideal for businesses and legal teams seeking automated, real-time trademark status monitoring and analysis.
Trademark Status Monitoring Workflow
Node Count | 11 – 20 Nodes |
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Nodes Used | @n8n/n8n-nodes-langchain.agent, @n8n/n8n-nodes-langchain.embeddingsHuggingFace, @n8n/n8n-nodes-langchain.lmChatHf, @n8n/n8n-nodes-langchain.memoryBufferWindow, @n8n/n8n-nodes-langchain.textSplitterCharacterTextSplitter, @n8n/n8n-nodes-langchain.toolVectorStore, @n8n/n8n-nodes-langchain.vectorStorePinecone, googleSheets, stickyNote, webhook |
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