{"id":5077,"date":"2025-07-04T05:02:53","date_gmt":"2025-07-04T05:02:53","guid":{"rendered":"https:\/\/mailitics.com\/index.php\/2025\/07\/04\/harper-release-46-now-features-vector-indexing-to-bring-contextual-depth-to-ai-models-170356-aspx\/"},"modified":"2025-07-04T05:02:53","modified_gmt":"2025-07-04T05:02:53","slug":"harper-release-46-now-features-vector-indexing-to-bring-contextual-depth-to-ai-models-170356-aspx","status":"publish","type":"post","link":"https:\/\/mailitics.com\/index.php\/2025\/07\/04\/harper-release-46-now-features-vector-indexing-to-bring-contextual-depth-to-ai-models-170356-aspx\/","title":{"rendered":"Harper Release 4.6 Now Features Vector Indexing to Bring Contextual Depth to AI Models"},"content":{"rendered":"<p>    Harper Release 4.6 Now Features Vector Indexing to Bring Contextual Depth to AI Models<br \/>\n \t<BR><br \/>\n<BR><\/BR><br \/>\n    <!-- no image --><br \/>\n \t<BR><br \/>\n<BR><\/BR><\/p>\n<div>Harper, bringing &#8220;next-level web performance to a digital-first world,&#8221; is releasing version 4.6 of its composable application platform, featuring several enterprise-grade components, chief among them the addition of vector indexing for the efficient storing and retrieving of high-dimensional vector data. For large digital brands with extensive product catalogues, the introduction to AI-enhanced search helps accelerate the customer&#8217;s journey and time-to-purchase.<\/div>\n<p> \t<BR><br \/>\n <BR><\/BR><\/p>\n<p> \t<BR><br \/>\n<BR><\/BR><br \/>\n<a href=\"https:\/\/www.dbta.com\/Editorial\/News-Flashes\/Harper-Release-46-Now-Features-Vector-Indexing-to-Bring-Contextual-Depth-to-AI-Models-170356.aspx\">Go to dbta<\/a><br \/>\n \t<BR><br \/>\n <BR><\/BR><\/p>\n","protected":false},"excerpt":{"rendered":"<p>Harper Release 4.6 Now Features Vector Indexing to Bring Contextual Depth to AI Models Harper, bringing &#8220;next-level web performance to a digital-first world,&#8221; is releasing version 4.6 of its composable application platform, featuring several enterprise-grade components, chief among them the addition of vector indexing for the efficient storing and retrieving of high-dimensional vector data. For [&hellip;]<\/p>\n","protected":false},"author":2,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[60],"tags":[66],"class_list":["post-5077","post","type-post","status-publish","format-standard","hentry","category-dbta","tag-dbta"],"_links":{"self":[{"href":"https:\/\/mailitics.com\/index.php\/wp-json\/wp\/v2\/posts\/5077"}],"collection":[{"href":"https:\/\/mailitics.com\/index.php\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/mailitics.com\/index.php\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/mailitics.com\/index.php\/wp-json\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"https:\/\/mailitics.com\/index.php\/wp-json\/wp\/v2\/comments?post=5077"}],"version-history":[{"count":0,"href":"https:\/\/mailitics.com\/index.php\/wp-json\/wp\/v2\/posts\/5077\/revisions"}],"wp:attachment":[{"href":"https:\/\/mailitics.com\/index.php\/wp-json\/wp\/v2\/media?parent=5077"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/mailitics.com\/index.php\/wp-json\/wp\/v2\/categories?post=5077"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/mailitics.com\/index.php\/wp-json\/wp\/v2\/tags?post=5077"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}