This n8n workflow automates the discovery, research, and validation of business entities, concepts, and terms. It integrates multiple data sources including a vector database, Wikipedia, and live web research to create comprehensive and accurate entity profiles. The workflow begins with a manual trigger or an external workflow invocation, then checks for existing data to prevent duplication. If new research is needed, it uses AI-powered agents to gather definitions, examples, related entities, and misconceptions. After validation, the profiles are stored in a knowledge base, building an evolving, authoritative terminology resource. This automation is ideal for content teams, business analysts, compliance officers, and knowledge managers aiming to maintain updated, consistent, and validated entity information.
Automated Entity Research & Validation System
Node Count | >20 Nodes |
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Nodes Used | @n8n/n8n-nodes-langchain.agent, @n8n/n8n-nodes-langchain.chainLlm, @n8n/n8n-nodes-langchain.documentDefaultDataLoader, @n8n/n8n-nodes-langchain.embeddingsOllama, @n8n/n8n-nodes-langchain.lmChatOpenAi, @n8n/n8n-nodes-langchain.outputParserStructured, @n8n/n8n-nodes-langchain.textSplitterCharacterTextSplitter, @n8n/n8n-nodes-langchain.toolWikipedia, @n8n/n8n-nodes-langchain.toolWorkflow, @n8n/n8n-nodes-langchain.vectorStoreQdrant, executeWorkflowTrigger, if, manualTrigger, merge, set, stickyNote |
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