Latenode
Google drive
Pinecone

Automated knowledge management: Sync Google docs, get AI answers

This automation system is designed to help companies efficiently manage their internal knowledge and provide accurate, context-aware answers to employee queries. It automatically indexes new and updated company documents stored in Google Drive using the Gemini AI API for embeddings and the Pinecone vector database for storage.

When an employee submits a question, the system retrieves the most relevant document sections and generates a comprehensive response using the Gemini Chat Model. The system also maintains short-term memory to enable more natural and contextual conversations. This solution helps companies centralize their knowledge, improve employee productivity, and deliver high-quality information to their workforce.

Updated Apr 2, 2026Est. run: 14sEst. cost: $0.0009
How Latenode estimates time and cost

Latenode bills workflow runs in credits: 1 credit = 30 seconds of processing. Minimum charge per run depends on your plan. Plug-and-Play (PnP) AI nodes are billed separately—each PnP token is $1 USD, charged pay-as-you-go at vendor cost plus a small processing fee, with no API keys required.

Full pricing — how credits work →
AI agents & chatbots

Workflow preview

What this template does

  • Indexes new and updated company documents stored in Google Drive
  • Stores document embeddings in Pinecone vector database for fast retrieval
  • Retrieves most relevant document sections to answer employee queries
  • Generates comprehensive responses using the Gemini Chat Model
  • Maintains short-term memory to enable contextual conversations

How it works

1
Trigger

Monitor Google Drive for new and updated company documents

The system continuously watches the company's Google Drive for any new or updated documents that may contain useful knowledge and information.

2
Action

Fetch relevant documents from Google Drive

When new or updated documents are detected, the system automatically downloads them from Google Drive for further processing.

3
Logic

Process documents and generate embeddings

The system splits the downloaded documents into smaller text chunks and generates semantic embeddings for each chunk using the Gemini AI API. This allows the system to understand the content and context of the information.

4
Action

Index documents in Pinecone vector database

The text chunks and their corresponding embeddings are then stored in the Pinecone vector database, enabling efficient retrieval and matching of relevant information.

5
Trigger

Receive user questions through chat interface

When an employee submits a question through the chatbot interface, the system is triggered to begin the process of providing a relevant and comprehensive answer.

6
Action

Retrieve relevant document chunks from Pinecone

The system queries the Pinecone vector database to find the most relevant text chunks that are related to the user's question.

7
AI

Generate a comprehensive answer using the Gemini Chat Model

The system uses the Gemini Chat Model to analyze the retrieved document chunks and generate a comprehensive, context-aware answer to the user's question.

8
Logic

Provide short-term memory for more natural conversations

The system maintains short-term memory to enable more natural and contextual conversations, allowing it to better understand the user's intent and provide more relevant information over the course of the chat.

Requirements

Obtain API key and access credentials for the Gemini AI API
Establish a connection to the Pinecone vector database to store and retrieve document embeddings
Configure Google Drive API credentials and access permissions to retrieve company documents
Implement a chatbot interface that can receive user queries and display responses

FAQ

Common questions about this template

Each run uses credits on your Latenode plan. We charge for processing time (1 credit = 30 seconds). Your actual cost depends on your plan and how long the run takes. See pricing plans for plans and how credits work.
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