Tools and best practices for modernizing search with AI
Being able to efficiently access enterprise data is just as critical as being able to store, manage, or secure it; despite its importance, traditional enterprise search continues to plague many organizations, bringing down productivity and reducing positive business outcomes.
Joined by a variety of search experts, KMWorld held a webinar, Supercharging Your Search Capabilities With AI, ML, and NLP, to surface the ways in which archaic search strategies can be catapulted into the future with an array of technologies—including AI, ML, and natural language processing (NLP)—in conjunction with best practices, ultimately driving data accessibility, productivity, and innovation across an enterprise.
John Lewis, Ed.D., CKO at SearchBlox, posed a question: What is the most-used hyperlink on the internet? Unfortunately for any enterprise, the answer is “BACK,” a notable symptom of poor end user search experiences leading to low retention.
The traditional response to delivering relevant information to end users exists as the infamous FAQ page—which has left a trail of unintended consequences. Most of users’ questions are ignored, and the FAQ document itself is riddled with duplicate content that is difficult to keep in sync.
Lewis then offered SearchBlox’s SmartFAQs as the answer to optimizing the traditional FAQ, a solution delivering automatically managed FAQs (with a human-in-the loop) based on an entire range of content, kept in sync with enterprise content. By providing precise answers and contextual links, SmartFAQs entirely optimize the end user search experience by innovating on outdated methods.
Additionally, Lewis pointed to SearchBlox’s Enterprise Search—a fully managed enterprise search solution—and SearchAI—a collection of AI tools that supercharge search—as crucial tools in modernizing the search experience, designed to be operated in tandem for maximum efficiency.
Sean Martin, CTO and co-founder at Cambridge Semantics, picked up the conversation by focusing on how generative AI can transform organization search processes. The promises of this technology in its application to search are vast; searching with everyday language, context-aware understanding, streamlined data exploration, and enhanced decision-making are all components that any enterprise would want to get their hands on.
Enter Cambridge Semantics’ Knowledge Guru, a conversational BI system integrating OpenAI's Chat LLM with CSI's Anzo Knowledge Graph Platform that simplifies generative AI search at enterprise scale in existing data infrastructures. Knowledge Guru takes the ontology of an enterprise as an input to understand the domain and avoid LLM hallucinations, allowing users to interact with knowledge graphs in their natural language, receiving real-time, precise answers that propel decision-making.
According to David Seuss, CEO at Northern Light, question answering is at the heart of the business use case for generative AI.
This is why Northern Light’s solution, the SinglePoint Platform, innovates on search to put research-driven answers in the hands of people who need it, when they need it. As a custom-built enterprise knowledge management platform that seamlessly integrates and enables full-text search of all an organization's research resources, SinglePoint leverages GPT-3.5 Turbo and NLP processing flows to inject enterprise data with context and relevance.
SinglePoint provides citations and links to jumpstart users on their research journey, summarizing various documents to deliver an accurate query response. The platform handles a wide variety of content types—such as business and technology news, market research, analysis reports, journal articles, and more—to arm its users with extensive, copyright-compliant responses, greatly accelerating and optimizing research processes.
Following Seuss, Ryan Welsh, founder and CEO at Kyndi, took webinar viewers on a deep-dive into the prospects of an answer engine as compared to search engines; essentially, answer engines are beginning to replace search engines due to their more relevant query responses.
While search engines provide a list of pages or links that match a keyword in the query, answer engines deliver immediate, accurate, contextually relevant, and trustworthy answers to queries in a single click. The benefits are abundantly obvious, but how do enterprises effectively implement answer engines to tackle search inefficiencies?
Like others before him, Welsh directed viewers’ attention to generative AI, the foundation of any enterprise-scale answer engine. Kyndi offers a selection of search solutions—including Kyndi Clarity for self-service agent centers and Kyndi Natural Language Search for delivering highly relevant, context-driven information—to aid in enterprise implementation of generative AI for more effective search.
Welsh also emphasized the use of analytics-guided content curation, where an enterprise can leverage Kyndi’s technology to gain visibility into users’ behaviors and content needs to curate a search-response process that meets users' unique needs.
For an in-depth discussion on modernizing enterprise search with informative demos, you can view an archived version of the webinar here.
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