Build production RAG systems and vector databases

Design Retrieval-Augmented Generation systems with embeddings

When building domain-specific QA systems that ground responses in corpus documents via semantic search.

• · Knowledge corpus, query types, retrieval requirements

• · RAG pipeline architecture
• · embedding model choice
• · retriever configuration
• · reranking strategy

• · Vector DB
• · Embedding models
• · LLM

• · Necessary tools or libraries available

• · Misunderstanding of requirements
• · Incomplete or outdated examples

• · Peer reviewed
• · Applied successfully to similar context
• · Source documented