A practical playbook to optimize retrieval pipelines for search and RAG: metrics, chunking, hybrid retrieval, ANN tuning, re-ranking, and efficiency.
A practical, end-to-end guide to designing, deploying, and operating embedding-based similarity search in production.
A practical, end-to-end guide to RAG evaluation metrics—from retrieval and grounding to faithfulness, relevance, and online impact.
Practical strategies to optimize LLM context windows—reduce cost and latency while preserving accuracy with RAG, chunking, compression, caching, and evaluation.
Build a production-ready tutorial for knowledge graph–enhanced AI retrieval: schema, ingestion, Cypher, hybrid search, and evaluation.
