A chat assistant with memory and answers from your documents

The assistant remembers the conversation and answers from your materials; new documents are picked up from a folder, and the chat history is logged and emailed to you.

  • Remembers the conversation context, not answering blind
  • Leans on your documents, not general knowledge
  • New files from a folder feed the knowledge base themselves
  • The chat history is logged and emailed to you
Google DriveDefault Data LoaderEmbeddings OpenAIGoogle Sheets ToolPinecone Vector Store

How it works

To connect Pinecone and Keap, you don't need a developer: a ready-made scenario links them in minutes.

  1. Starts when: When chat message received
  2. Then: Format Data For AI Agent
  3. Then: AI Agent (Chat Composer)
  4. Then: Conversation Logging
  5. Then: Short-Term Memory
  6. Then: Output Parser (JSON Enforcement)
  7. Then: OpenAI Chat Model
  8. Starts when: Google Drive Trigger
  9. Then: Download file
  10. Then: Pinecone Vector Store Insert
  11. Then: Default Data Loader
  12. Then: Recursive Character Text Splitter
  13. Then: Embeddings OpenAI
  14. Starts when: Schedule Trigger
  15. Then: Get Data from Sheet.
  16. Then: Aggregate
  17. Then: Convert Data to file
  18. Check: Check File Exist
  19. If yes: Send Chat History with attachment
  20. Then: Get Previous Content from Sheet
  21. Then: Pinecone Vector Store Query for Knowledge Base
  22. Then: Embeddings OpenAI Query for Chat modal

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