# Relevance tuning The configuration of an intelligent search algorithm can be extremely complicated. So, we re-imagined how you can build search by creating pipelines. [Pipelines](https://www.search.io/blog/introducing-pipelines) break down search configuration into smaller pieces that can be easily mixed, matched, and combined to create an incredibly powerful search experience. Pipelines are highly composable and extendable. There are two kinds of pipelines to consider: Record pipelines and Query pipelines. * [Record pipelines](https://docs.search.io/developer-documentation/fundamentals/pipelines/record-pipelines) define how your product data is processed on ingest * [Query pipelines](https://docs.search.io/developer-documentation/fundamentals/pipelines/query-pipelines) define how your queries are constructed Search.io automatically generates initial pipelines for you that you can modify or append later on via our built-in pipeline editor. When you first set up search.io, the auto-detecting onboarding flow allows you to: 1. Mark which fields are most important in ranking 2. Select how to train autocomplete and spelling 3. Generate a schema and initial pipelines But there is much more you can do with pipelines. In the [admin console](https://app.search.io), look for the Search Settings section; in particular, [Relevance](https://app.search.io/collection/pipelines/relevance) and [Indexing](https://app.search.io/collection/pipelines/record): ![](https://3882858970-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2FVeIbtsTcQaqaNeKzLbbU%2Fuploads%2F9imoUz715OJKC2pBEf1N%2Frelevance-tuning.png?alt=media\&token=ed378979-7e60-4289-9615-c133fd191e69) For more information on tuning relevance and ranking, head over to our [Search settings](https://docs.search.io/documentation/fundamentals/search-settings) docs. --- # Agent Instructions: Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question. Perform an HTTP GET request on the current page URL with the `ask` query parameter: ``` GET https://docs.search.io/documentation/guides/e-commerce/relevance-tuning.md?ask= ``` The question should be specific, self-contained, and written in natural language. The response will contain a direct answer to the question and relevant excerpts and sources from the documentation. Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.