Building AI applications with RAG? 🤖

The vector database decision alone can mean the difference between spending $50/month or $5,000/month.

This guide covers the implementation decisions that actually matter:

📊 Pinecone vs Weaviate vs Chroma for different scales

💰 Choosing between OpenAI's text-embedding-3-small and more expensive alternatives

✂️ Chunking strategies that balance retrieval quality with LLM context windows

🔍 Query optimization patterns like hybrid search and reranking

Includes cost formulas so you can estimate your AI infrastructure spend before you commit, plus optimization levers that cut costs without sacrificing quality.

Read the full implementation blueprint ↓