4 posts
How to evaluate embedding model quality on your own data in 2026: recall@k, MRR, nDCG, building a golden set, and pitfalls of offline and online evaluation.
How to choose a document chunking strategy for RAG in 2026: fixed size, recursive, semantic, tables, and code. Concrete sizes and overlap.
How to select an embedding model for RAG with Polish documents in 2026: criteria, comparison of multilingual and monolingual models, evaluation on your own data.
What are embeddings and semantic search, how they work in practice, and when to implement them in a company knowledge base or product.
