What Is Cortex Search in Snowflake?

For example:

Query: "cloud storage problem"

The system may prioritize records containing the words "cloud," "storage," and "problem."

Semantic Search

Semantic search places greater emphasis on understanding the meaning behind a query. 

For example:

Query: "Why can't I access my files stored online?"

Even if the source document uses terms such as "cloud storage access failure," the system can identify that the content is related to the user's question.

This can be especially useful for knowledge bases and customer-support applications where people naturally use different words to describe the same problem.

Why Use Cortex Search in Snowflake?

One major advantage is that organizations can build search capabilities while keeping their data within their Snowflake environment.

Instead of moving business information into a separate search platform for every use case, teams can use Snowflake capabilities to create search experiences around their existing data.