A metasearch engine is an information retrieval solution that connects to multiple search engines to fetch results for the same query and then produce a blended result set. Metasearch engines take a query from a user and immediately distribute the query across search engines for results. After gathering the data, the metasearch engine ranks and displays the results. Best in class metasearch or federated solutions will normalize relevancy from the disparate sources.
What Does Metasearch Engine Do?
Metasearch engines are a unique type of search engine that operates distinctly. Unlike traditional search engines, metasearch engines don’t rely on their own database of indexed pages. Instead, they search for and retrieve results from multiple search engines, and then combine or compile these results into a single set of results. This process of collating results from different search engines allows metasearch engines to provide users with a more comprehensive and diverse set of results.
How Does A Metasearch Engine Work
Here’s a bit more on how metasearch engines do their search:
Querying: When you search for something, the metasearch engine sends your question to several other search engines.
Collecting Results: It then gathers all the answers it gets from these different search engines.
Ranking: The metasearch engine sorts these results based on relevance, quality, and, sometimes, user preferences.
Displaying: Finally, it shows you a combined list of results from all those sources.
Swirl is a metasearch engine designed for your enterprise. It takes data from different sources and search indexes and then displays them in a unified results space.
This enables you to easily get results from different data sources without moving any data. And with the support of new cutting-edge AI features. You can now use Large Language Models on your search results to perform Retrieval Augmented Generation (RAG) on your metasearch results.