A developer rebuilt a high-throughput RAG system using DeepSeek for inference and Weaviate for vector retrieval, fronted by Global API's unified gateway. This stack handles 12,000 RAG requests per minute with a p99 latency reduced from 8.4s to 1.9s, achieves 99.97% availability across three regions, and reduces inference costs by 40-65% compared to direct use of GPT-4o. Key practices include semantic caching, streaming responses, model routing by query complexity, and multi-region failover for SLA compliance.
Use Case
Opening the operator briefing
Pulling the full operator breakdown, tooling context, and verification notes.
