When you need Documentdefaultdataloader and Informationextractor talking to each other, here are the 47 n8n workflows in the catalog that already do it. Each is integration-tagged and privacy-stripped — copy the JSON and import.
Workflows that pair Documentdefaultdataloader with Informationextractor
Api Schema Extractor. Uses manualTrigger, httpRequest, splitOut, textSplitterRecursiveCharacterTextSplitter. Event-driven trigger; 88 nodes.
Wait Splitout. Uses manualTrigger, httpRequest, splitOut, textSplitterRecursiveCharacterTextSplitter. Event-driven trigger; 88 nodes.
This workflow automates the process of discovering and extracting APIs from various services, followed by generating custom schemas. It works in three distinct stages: research, extraction, and schema
crawl4 ai. Uses documentDefaultDataLoader, textSplitterCharacterTextSplitter, vectorStoreSupabase, embeddingsOllama. Scheduled trigger; 65 nodes.
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.
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.
BambooHR AI-Powered Company Policies and Benefits Chatbot. Uses manualTrigger, documentDefaultDataLoader, embeddingsOpenAi, textSplitterRecursiveCharacterTextSplitter. Event-driven trigger; 50 nodes.
BambooHR AI-Powered Company Policies and Benefits Chatbot. Uses manualTrigger, documentDefaultDataLoader, embeddingsOpenAi, textSplitterRecursiveCharacterTextSplitter. 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
This workflow enables companies to provide instant HR support by automating responses to employee queries about policies and benefits: Retrieves company policies, benefits, and HR documents from Bambo
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 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
local_RAG. Uses documentDefaultDataLoader, textSplitterRecursiveCharacterTextSplitter, chatTrigger, memoryBufferWindow. Event-driven trigger; 39 nodes.
This n8n workflow builds a self-improving AI agent for handling email responses. It integrates Gmail for incoming messages, uses an AI agent with a Supabase vector store for knowledge retrieval, draft
Customer Insights With Qdrant, Python And Information Extractor. Uses manualTrigger, html, splitOut, documentDefaultDataLoader. Event-driven trigger; 37 nodes.
Splitout Code Export. Uses manualTrigger, html, splitOut, documentDefaultDataLoader. Event-driven trigger; 37 nodes.
This n8n template is one of a 3-part series exploring use-cases for clustering vector embeddings: Survey Insights Customer Insights Community Insights
My workflow 3. Uses formTrigger, splitInBatches, lmChatGoogleGemini, httpRequest. Event-driven trigger; 36 nodes.
See more Documentdefaultdataloader workflows · Informationextractor workflows
FAQ
How do I trigger a Informationextractor action from Documentdefaultdataloader?
Most workflows in this list use either a Documentdefaultdataloader webhook trigger (real-time) or a polling trigger (every N minutes). From there, downstream Informationextractor nodes handle the action. Open any workflow's detail page to see the exact node graph.
Do I need both a Documentdefaultdataloader and a Informationextractor 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 Documentdefaultdataloader → Informationextractor 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.