Build a RAG-based Agent with MindsDB

In this Technical Exploration, Jonny and Tarik show how to build a fully functioning RAG-based AI agent using MindsDB, turning internal data from Postgres, Slack, or Google Drive into a queryable knowledge base powered by semantic search. You'll see how to: Convert internal documents into a semantic knowledge base Make Google Drive & Slack data queryable in minutes Build a custom AI Agent on top of your knowledge bases Run MindsDB locally with Docker Use SQL to configure agents, connectors, and knowledge bases Expose your agent through a simple API for app integration We also touch on: Chunking & embedding strategies Local vs. cloud LLMs How MindsDB compares to full ETL approaches Resources: Demo code: https://github.com/datamindedbe/demo-technology-exploration/ Previous episode (PyAirbyte): https://youtu.be/eLUQrSqP-ns Click here to watch a video of this episode. Full playlist: https://www.youtube.com/playlist?list=PLJ_da7qdfL80rA7byzC_CmyrfJWjcCTnb Note: This video is not sponsored or affiliated with MindsDB. Creators & Guests Jonny Daenen - Host Tarik Jamoulle - Guest Chapters: (00:00) - Intro: What is MindsDB? (02:03) - Scope and dataset (03:08) - Quick tour: connectors & UI (06:34) - Components: Source, Knowledge Base & Agent (06:55) - Agent demo + how MindsDB queries data (08:36) - The code: getting MindsDB running (11:27) - Q&A: embedding times & creating your agent (14:03) - A Slack agent in 5 minutes (17:19) - Multi-knowledge-base agents (18:23) - Q: Integrating with SDK & MCP (19:31) - Takeaways Data & AI: Technology Explorations is a biweekly show from Dataminded. Each episode a Dataminded engineer demos a tool or technique worth knowing about -- working code, honest takes, no hype. Music by Aleksandr Karabanov from Pixabay