Recently, we were experimenting with elastic search and it capability for using vector search as our sarch engine.

The banking industry is constantly evolving, driven by the need to enhance security, streamline operations, and improve risk management. Traditional search methods often fall short in meeting these demands due to their reliance on exact keyword matches, which can miss critical insights. Semantic search, with its ability to understand context and intent, offers a powerful solution to these challenges. Let's explore how semantic search can transform banking.

In the realm of information retrieval, traditional keyword-based search methods often fall short in understanding the true intent behind user queries. This limitation arises from their reliance on exact keyword matches, which can miss the nuanced meanings and relationships between words. Semantic search addresses this challenge by leveraging advanced techniques in natural language processing (NLP) and machine learning to interpret the context and semantics of queries.

Imagine you're at a massive library, but instead of searching for books by their titles, you can find them based on the ideas and themes they contain. That's the magic of vector search! Traditional keyword searches can be limiting, often needing deeper connections between words. Vector search, on the other hand, uses the power of text embeddings to understand the semantic meaning behind the text, making your searches more intelligent and relevant.