Frequently asked questions
Drupal supports enterprise search through Apache Solr, providing full-text search with faceting, content boosting, binary file indexing, date-based relevance scoring, and autocomplete. Morpht enhances this foundation with AI-powered search improvements including Sajari integration, regime-based result filtering (adjusting results based on user context), confusion matrix analysis to remove false positives, and search performance analytics. For complex government sites with large content volumes, well-configured search is often the single highest-impact improvement in user satisfaction.
Basic search handles simple keyword matching well, but large content repositories (thousands of publications, forms, fact sheets) typically need faceted search, relevance tuning, and synonym/typo handling to be genuinely usable; this is where dedicated search solutions (like Apache Solr integrations, common in enterprise Drupal builds) earn their cost over core search.
Search is often the safety net for weak IA. When users can't find something through navigation, they turn to search, so a site with strong faceted search can partially compensate for imperfect navigation structure, though the two should ideally be designed together rather than search being an afterthought.
Yes. AI-assisted search (semantic/natural-language search rather than pure keyword matching) is an active area of Drupal development, and can meaningfully improve findability for content-heavy sites where users don't always search using the exact terms content authors used. Though it needs to be implemented with the same accuracy and governance scrutiny as any other AI feature on a government site.
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