When you need OpenAI Embeddings and Qdrant Vector Store talking to each other, here are the 128 n8n workflows in the catalog that already do it. Each is integration-tagged and privacy-stripped — copy the JSON and import.
Workflows that pair OpenAI Embeddings with Qdrant Vector Store
This workflow implements an advanced AI automation agent (OpenClaw Agent) that interacts with users through Telegram and integrates multiple AI models, external tools, and cloud services to automate c
Alfred (funcional). Uses gmailTool, googleCalendarTool, gmail, embeddingsOpenAi. Event-driven trigger; 83 nodes.
This comprehensive workflow bundle is designed as a powerful starter kit, enabling you to build a multi-functional AI assistant on Telegram. It seamlessly integrates AI-powered voice interactions, an
Agent IA Projet Client. Uses executeWorkflowTrigger, lmChatOpenAi, toolWorkflow, vectorStoreQdrant. Event-driven trigger; 79 nodes.
HeyDinastia. Uses executeCommand, httpRequest, youTube, postgres. Webhook trigger; 66 nodes.
Build a powerful, customizable AI chatbot for your WordPress website that intelligently retrieves posts, answers questions, and engages in natural conversations. This complete solution handles content
I originally started to template to ask questions on the "n8n @ scale office-hours" livestream videos but then extended it to include the latest videos on the official channel.
Iroko-chatbot-green-API. Uses toolCalculator, agent, n8n-nodes-whatsapp-green-api, chatTrigger. Webhook trigger; 54 nodes.
Code Extractfromfile. Uses manualTrigger, sort, httpRequest, compression. Event-driven trigger; 50 nodes.
🤖 AI Powered RAG Chatbot for Your Docs + Google Drive + Gemini + Qdrant. Uses documentDefaultDataLoader, textSplitterTokenSplitter, vectorStoreQdrant, splitInBatches. Event-driven trigger; 50 nodes.
2464. Uses httpRequest, compression, editImage, documentDefaultDataLoader. Event-driven trigger; 50 nodes.
Workflow 2464. Uses httpRequest, compression, editImage, documentDefaultDataLoader. Event-driven trigger; 50 nodes.
This workflow creates a powerful RAG (Retrieval-Augmented Generation) chatbot that can process, store, and interact with documents from Google Drive using Qdrant vector storage and Google's Gemini AI.
Are you a popular tech startup accelerator (named after a particular higher order function) overwhelmed with 1000s of pitch decks on a daily basis? Wish you could filter through them quickly using AI
Splitout Code. Uses stickyNote, toolWorkflow, mcpTrigger, executeWorkflowTrigger. Event-driven trigger; 44 nodes.
This n8n implementation exposes other cool API features from Qdrant such as facet search, grouped search and recommendations APIs. With this, we can build an easily customisable and maintainable Qdran
Workflow 3636. Uses toolWorkflow, mcpTrigger, executeWorkflowTrigger, httpRequest. Event-driven trigger; 44 nodes.
Survey Insights With Qdrant, Python And Information Extractor. Uses embeddingsOpenAi, documentDefaultDataLoader, textSplitterRecursiveCharacterTextSplitter, googleSheets. Event-driven trigger; 42 node
Splitout Code. Uses embeddingsOpenAi, documentDefaultDataLoader, textSplitterRecursiveCharacterTextSplitter, googleSheets. Event-driven trigger; 42 nodes.
This n8n template is one of a 3-part series exploring use-cases for clustering vector embeddings: Survey Insights Customer Insights Community Insights
🤖📈 This workflow is my personal solution for the Agentic Arena Community Contest, where the goal is to build a Retrieval-Augmented Generation (RAG) AI agent capable of answering questions based on a p
Email AI Auto-responder. Summerize and send email. Uses emailReadImap, lmChatOpenAi, emailSend, vectorStoreQdrant. Event-driven trigger; 41 nodes.
Email AI Auto-responder. Summerize and send email. Uses emailReadImap, lmChatOpenAi, emailSend, vectorStoreQdrant. Event-driven trigger; 41 nodes.
This workflow transforms a Google Drive folder into an intelligent, searchable knowledge base and provides a chat agent to query it. It’s composed of two distinct flows: An ingestion pipeline to proce
See more OpenAI Embeddings workflows · Qdrant Vector Store workflows
FAQ
How do I trigger a Qdrant Vector Store action from OpenAI Embeddings?
Most workflows in this list use either a OpenAI Embeddings webhook trigger (real-time) or a polling trigger (every N minutes). From there, downstream Qdrant Vector Store nodes handle the action. Open any workflow's detail page to see the exact node graph.
Do I need both a OpenAI Embeddings and a Qdrant Vector Store account?
Yes — n8n connects to each integration via your own credentials. AutomationFlows strips credential IDs before publishing, so you'll add your own.
Are these OpenAI Embeddings → Qdrant Vector Store workflows free?
Yes — every workflow on AutomationFlows is free to browse and copy. Pro adds a multi-signal QualityScore on every workflow plus bulk JSON download.