Building high-performance compound AI applications with MongoDB Atlas and Baseten

This post introduces the concept of compound AI and details how Baseten Chains, combined with MongoDB Atlas, can be used to build high-performance compound AI systems like RAG. It highlights the importance of appropriate hardware allocation (e.g., GPUs for LLM inference, CPUs for other tasks) and minimizing network overhead to eliminate bottlenecks. The post also discusses batching and throughput considerations in multi-stage AI workflows.