{"type":"video","version":"1.0","html":"<iframe src=\"https://www.loom.com/embed/1a65146ae73e4348879df5e88d741b9f\" 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/1a65146ae73e4348879df5e88d741b9f-4dd591058c8bd4b3.gif","duration":420.435,"title":"Modernizing a Rideshare Operations Platform","description":"This Loom discusses how the speaker modernized a Rideshare/taxi Management operational platform for a Canadian taxi company, starting from a PHP(Laravel)-based system and expanding to Python-driven services. They describe recreating and documenting the business operation, then addressing a key challenge: continuously growing driver data that previously caused manual handling by managers and operations teams. To improve driver assignment and routing, they implemented components using Python, including neural services and AI model iterations, and moved functionality into FastAPI services deployed on Amazon Web Services. They also implemented AWS Lambda background jobs, focusing on scheduling and synchronization while thoroughly retesting on local and staging environments to avoid interrupting the business."}