AutomationFlows › AI & RAG › Customer Insights with Qdrant & OpenAI

Customer Insights with Qdrant & OpenAI

Original n8n title: Customer Insights with Qdrant, Python and Information Extractor (document Default Data Loader)

ByJimleuk @jimleuk✓ on n8n.io

This n8n template is one of a 3-part series exploring use-cases for clustering vector embeddings: Survey Insights Customer Insights Community Insights

Event trigger★★★★★ complexityAI-powered37 nodesDocument Default Data LoaderText Splitter Recursive Character Text SplitterOpenAI EmbeddingsHTTP RequestOpenAI ChatGoogle SheetsExecute Workflow TriggerQdrant Vector Store
AI & RAG Trigger: Event Nodes: 37 Complexity: ★★★★★ AI nodes: yes Added:

This workflow corresponds to n8n.io template #2373 — we link there as the canonical source.

This workflow follows the Documentdefaultdataloader → OpenAI Embeddings recipe pattern — see all workflows that pair these two integrations.

The workflow JSON

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About this workflow

    
This n8n template is one of a 3-part series exploring use-cases for clustering vector embeddings: Survey Insights Customer Insights Community Insights

    
Source: https://n8n.io/workflows/2373/ — original creator credit. Request a take-down →

    
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