welcome to customer success platform I am now going to walk you through the AI search working model I would like to keep this demo short and insightful this is the homepage of our CSP if you see on the top right corner there is a traditional search box where a user can search for AI enabled content suggested results are displayed as you type through the desired content in the search box let's now explore the genius results generated by AI search wherein if you type a keyword called request a list of related actionable items are obtained based on the given keyword going further we will navigate through a couple of AI search implementations Incorporated in CSP platform the first one being projects which is our internal data source or the table that resides within the platform to make this a more refined search the user enters the project keyword in the search box the first row contains a set of navigation tabs allowing the user to seamlessly switch between different options the alt tab displays all the records having project keyword let's now navigate to the projects tab the UI view showcasing the details of the project are configured using evam templates furthermore these can be customized based on user requirements towards the left is the facets tab which are nothing but filters we can now filter the records by selecting relevant state or status let's say say if we want to see the projects which are in pending State we can select the pending State filter and all the projects which pending state are filtered the same goes for other filters towards the top right is the drop down that sorts the records based on most relevant newest and oldest results by default the option is set to most relevant this can be sorted as per user needs beneath the drop-down is a list view hyperlink that opens a new tab with all records in a listed view we shall now proceed to the next implementation which is knowledge articles similar to other relevant searches the search box here provides the functionality of displaying knowledge article records let's go with an example here I now type in a text in the search box as seen the records that are mostly frequently accessed are suggested upon searching all the knowledge articles relevant to the text in the search box are displayed moving forward to the final implementation SharePoint documents which is an external data source the search criteria is similar to that implemented in our AI search implementations when a search is commenced the records displayed here are those that are extracted from SharePoint which is an external data source the keyword typed in the search box not only displays the records containing the document name but also access the contents of the documents and extract that relevant doc document which has the given keyword so far we have covered the search experience that indexes data from both internal and external sources and displays relevant search results to the user we can draw an observation that the user interface and search criteria of the entire model is similar for both internal and external sources despite the fact that backend configuration for each search criteria varies one of the external data coming from surf viia Azure other from SharePoint via SharePoint online connector and the internal data that resides in platform itself we have now come to the end of this AI search demonstration thank you for watching