{"type":"video","version":"1.0","html":"<iframe src=\"https://www.loom.com/embed/d4183e4cfdee42cb835ac793eddd2da3\" frameborder=\"0\" width=\"1280\" height=\"960\" webkitallowfullscreen mozallowfullscreen allowfullscreen></iframe>","height":960,"width":1280,"provider_name":"Loom","provider_url":"https://www.loom.com","thumbnail_height":960,"thumbnail_width":1280,"thumbnail_url":"https://cdn.loom.com/sessions/thumbnails/d4183e4cfdee42cb835ac793eddd2da3-5aa6ad7b98efca38.gif","duration":264.558,"title":"Letting AI Agents to talk your data no matter where it's from","description":"Try it out: https://www.fused.io/canvas/fc_1rtdqA4hR99S9cQm6XfiCj?bounds=435%2C1727%2C2921%2C4472\n\nIn this video, I showcase how I've built a system to analyze supplier data using various data sources like Snowflake, Google Sheets, and AWS S3. I demonstrate how I can easily join this data in Python and expose it through an API for AI agents like Claude to access. By doing this, I can retrieve insights on top and bottom performing stores based on their ratings. If you're interested in exploring this further, I invite you to check out the canvas at Fuse.io where you can try it out for yourself."}