A focused embedding specialist that converts text into dense vector representations, optimized for retrieval and semantic similarity tasks. Built on the ModernBERT architecture, it handles longer context windows than traditional BERT-family models, making it more capable with longer documents. It produces embeddings rather than generating text, so it's a tool for search pipelines and similarity systems rather than a conversational partner.