Practical blueprint for an AI content personalization API: architecture, endpoints, models, metrics, latency, and safety—built to scale.
A practical, end-to-end guide to designing, deploying, and operating embedding-based similarity search in production.
A practical 2026 guide comparing vector vs. keyword search: principles, pros/cons, costs, evaluation, and when to choose hybrid—with code snippets.
Build a practical multi‑modal RAG system that retrieves from images and text using OCR, captions, CLIP embeddings, and vector search.
A practical guide to advanced chunking in RAG: semantic and structure-aware methods, parent–child indexing, query-driven expansion, and evaluation tips.
A practical guide to choosing RAG vs fine-tuning, with a clear decision framework, patterns, code sketches, and pitfalls.
