Four deployment patterns for AI agents are explored: batch deployment for scheduled bulk processing with high throughput, stream deployment for continuous real-time data pipeline processing, real-time deployment via APIs for instant user interactions, and edge deployment on user devices for privacy and offline functionality. Each pattern serves different performance requirements, with batch optimizing throughput, stream enabling continuous monitoring, real-time providing sub-second responses, and edge ensuring data privacy without server dependencies.
Sort: