SearchUnify's Facet Interpreter, powered by Agentic AI, analyzes user search queries in real-time, extracting key facets and discerning user intent. This intelligent feature, driven by Agentic AI, automatically identifies and pre-selects the most relevant facets, refining the faceted search experience to help users navigate directly to their desired results efficiently.
With Sticky Facets, Agentic AI remembers users' previous filter selections across searches, eliminating the need to reapply filters for every query. The system remembers individual filter selections across multiple searches, eliminating the need for repetitive re-application of filters. This personalized approach ensures a consistent and efficient search experience.
Agentic AI takes Auto Facets to the next level by dynamically personalizing search filters based on individual preferences, past interactions, and trending data. By automatically selecting the most relevant facets, Agentic AI ensures a faceted search experience that feels tailored to each user, enhancing engagement and satisfaction.
SearchUnify empowers administrators to optimize facet organization and customization through Agentic AI insights. While the platform automatically generates relevant facet types, administrators can refine these based on real-time user behavior, ensuring a more adaptive and effective faceted search experience.
Nested Facets powered by Agentic AI break down complex categories into more granular sub-categories, providing an organized, structured way for users to drill deeper into their search results. Agentic AI dynamically identifies relevant sub-categories to ensure no crucial classifications are missed, enhancing faceted search precision.
Gain deep insights into user search behavior with Agentic AI-powered analytics. Understand which facets are most frequently used, identify trending content types, and leverage these data-driven insights to continuously optimize your faceted search interface for maximum effectiveness.
Federated search with SearchUnify boosted our confidence in our knowledge base and online help center. Knowing our content would be easily accessible, we ramped up content creation by 44%. Consequently, customer complaints about self-service and documentation dropped by 24%.
Garrick Greenhalgh
MSHR, CSPO, Director of Global Technical Education and Community, Accela
With SearchUnify's AI, Bluebeam significantly enhanced our customer support, swiftly connecting them to needed resources. Improving our business is a core practice, and we're proud to be recognized for our collaboration with SearchUnify in achieving this.
Jim Atkinson
President and Chief Customer Officer, Bluebeam, Inc.
Faceted search is an advanced search method that enables users to filter results based on specific categories, or "facets," such as date, topic, or content type. This structured filtering system improves search accuracy and efficiency by allowing users to drill down into relevant information quickly, making it easier to locate precise answers.
Agentic AI dynamically personalizes and optimizes facets based on user behavior, creating a more intuitive and tailored experience.
Yes, both users and administrators can customize facets for a more personalized and relevant search experience.
Agentic AI analyzes the facets a user selects and provides related content recommendations based on those choices. This feature enriches the search experience by suggesting additional resources that align with the user’s interests, facilitating deeper exploration and engagement.
Yes, Agentic AI-powered search analytics give you insights into user engagement with various facets. This data includes which facets are most commonly used and the types of content users frequently access, enabling data-driven decisions to enhance and refine the faceted search experience.
Absolutely. Faceted search is designed to handle large, complex datasets by organizing information into manageable categories, enabling users to filter down results effortlessly. Agentic AI further enhances this by dynamically generating facets and adapting them to user needs, making it ideal for vast datasets.
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