RAG & Knowledge Basesfree

Build a chatbot on website content and Airtable data for RAG applications

by Alok KumarUpdated Aug 2026

RequiresOpenAI

AirtableOpenRouter

1/5

FLOWS

STEPS · 8

Run manually by an operator

On manual run, ingests website and Airtable data into a Pinecone vector store, then answers chat queries via an OpenAI/OpenRouter RAG agent.

Google Docs — Google Gemini

On manual run, indexes documents into Pinecone, then a Gemini agent retrieves context and writes outputs to Google Docs, Sheets, and Drive.

On manual trigger, answers queries via a Gemini and OpenAI agent over a Pinecone vector store built from Google Docs, Sheets, and Drive.

On manual run, loads Google Drive documents, splits them into context-aware chunks, embeds with Gemini, and stores vectors in Pinecone.