Robust to noisy data

Noisy data often contains errors, outliers, and irrelevant information that hinder an embedding model’s ability to discern meaningful patterns or relationships within the data. Our Embed model understands your data’s nuances, making it highly accurate even when dealing with noisy real-world datasets.

Better retrieval for RAG

The effectiveness of RAG is dependent on multiple components, including embedding models that power search systems to retrieve relevant information. Embed’s elevated accuracy facilitates highly relevant and fewer search results, saving time and computational resources for retrievals.