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· 9 min read
Fernando Guerra

Search technology has undergone an incredible transformation over the past few years. It began with simple, directory-based methods and evolved into sophisticated algorithms capable of interpreting the nuances of human language.

Mostly of the systems until today rely heavily on keyword matching. However, this approach has a lot of limitations, often overlooking the context or the true intent behind a user's query.

So the need for a more intelligent search became apparent. This need led to the rise of artificial intelligence (AI) in search technologies, giving birth to vector search, a method that understands queries and content at a much deeper level. By prioritizing context and semantics, vector search can discern the meaning behind words, providing more accurate and relevant results.

What is Search by Keywords?

Keyword-based search is the foundation upon which traditional search engines were built. It involves searching through documents to find matches for specified words or phrases. Despite its straightforward nature, this method has drawbacks---it lacks the ability to understand the context or the intent behind the search query. This limitation often results in a list of results that contain the keywords but may be irrelevant to what the user is actually looking for.