With the introduction of Sitecore XM Cloud, one of the biggest challenges was how we were going to handle search. Let’s remember that XM Cloud is a headless CMS and that it will deliver content through a rendering server. What this means is that our code shouldn’t run on the Sitecore CM server. This provides a challenge for search as we can’t implement it on the CM using Solr as we used to.

But not to fear, Sitecore thought about this and as part of its composable stack, introduced Sitecore Search 🎉

Sitecore Search is a solution that allows us to surface relevant content through AI-powered search. Its main features are:

• Fast, predictive search: Sitecore Search can suggest relevant content as visitors are typing, anticipating the visitor journey within milliseconds.
• AI-based personalization: Sitecore Search can understand and act upon individual visitors’ intent through AI and context-aware rules in real-time.
• Rich APIs and components: Sitecore Search provides you with tools to seamlessly embed content search, guided navigation, and promotion into any site.
• Deep content insights: Sitecore Search can measure engagement with themes and keywords across your content, going beyond URLs and clicks.
• Multilingual management: Sitecore Search can incorporate multiple languages at once into your search to simplify management and global relevance.

But most importantly for XM Cloud is that it’s a cloud-based solution. This means that it’s an independent application that runs on its own cloud and it’s able to scan content from our site and serve it through a set of APIs.

By using Sitecore Search, we maintain the headless architecture of XM Cloud and we get all the benefits of an AI-powered search platform.

In the next posts, we are going to go into detail about some important aspects of this platform before starting an actual implementation 😉