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RAG on living data

Automated workflow: RAG on living data. This workflow integrates 18 different services: notionTrigger, stickyNote, textSplitterTokenSplitter, vectorStoreSupabase, chainRetrievalQa.

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Why Use This Automation

The RAG on Living Data automation is a cutting-edge AI-powered solution that transforms how organizations process, analyze, and extract insights from dynamic document repositories. By leveraging advanced retrieval-augmented generation (RAG) techniques, this workflow automates intelligent document intelligence across knowledge management systems. Organizations can now automatically ingest, embed, and query complex data sources from Notion, Supabase, and other platforms, enabling real-time question answering and comprehensive content summarization without manual intervention.

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Time Savings

Save 8-12 hours per week on manual document research and analysis

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Cost Savings

Reduce knowledge management costs by $3,000-$5,000 monthly through automation

Key Benefits

  • Automatically transform unstructured documents into searchable, intelligent knowledge bases
  • Reduce manual research and content analysis time by up to 90%
  • Enable AI-powered question answering across multiple data sources
  • Create dynamic, self-updating knowledge repositories
  • Enhance decision-making with instant, contextual information retrieval

How It Works

The RAG on Living Data automation triggers scheduled data ingestion from multiple sources like Notion and Supabase. It uses OpenAI embeddings to convert documents into vector representations, enabling semantic search capabilities. The workflow then applies advanced retrieval techniques to split and process documents, creating a dynamic vector store. When triggered, the system can instantly generate summaries, answer complex queries, and extract key insights using chainable AI retrieval mechanisms.

Industry Applications

Research

Research institutions can create living literature reviews that automatically update with new publications, providing researchers instant access to the latest findings in their field.

Education

Universities can automatically aggregate research papers, lecture notes, and academic publications into a searchable knowledge base, enabling researchers to quickly find and synthesize information across departments.

Knowledge Management

Corporate learning and development teams can build intelligent document repositories that continuously evolve, making institutional knowledge instantly accessible to employees.