An assistant that answers from your documents

Upload documents — the scenario parses them, stores them in Qdrant Vector Store, and answers questions strictly from them.

  • Answers grounded in your documents
  • Upload through a simple form
  • Finds the right passage itself
  • The answer can be emailed to you
n8n FormPinecone Vector StoreEmbeddings Mistral CloudDefault Data Loader
Connect Qdrant Vector Store and goScriptera

How it works

To connect enkod and Qdrant Vector Store, you don't need a developer: a ready-made scenario links them in minutes.

  1. Starts when: On form submission4
  2. Then: split the binary item
  3. Check: Loop Over Items1
  4. Then: Aggregate1
  5. Then: Translator Agent
  6. Then: Analyzer Agent
  7. Then: Markdown
  8. Then: Code
  9. Then: Convert to File
  10. Then: Gmail
  11. Then: AI Agent
  12. Then: Information Extractor
  13. Then: Convert to File4
  14. Then: Pinecone Vector Store
  15. Then: Parsing the document
  16. Then: Check the parsing status
  17. Check: If2
  18. If yes: Provide the markdown
  19. Then: Google Gemini Chat Model5
  20. Then: Google Gemini Chat Model6
  21. Then: Google Gemini Chat Model
  22. Then: Google Gemini Chat Model1
  23. Then: Embeddings Mistral Cloud
  24. Then: Default Data Loader
  25. Then: Recursive Character Text Splitter
  26. Starts when: When chat message received
  27. Then: Question and Answer Chain
  28. Then: AI Agent1
  29. Then: Google Gemini Chat Model2
  30. Then: Vector Store Retriever
  31. Then: Pinecone Vector Store1
  32. Then: Embeddings Mistral Cloud1
  33. Then: Google Gemini Chat Model3

You can launch this enkod + Qdrant Vector Store integration in Scriptera: describe the task in plain words — the scenario is built, launched and monitored for you.

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