Instantly Build Conversational Experiences
by processing the enterprise knowledge repository
A virtual assistant’s ability to understand and answer different variations of the same question is central to its success. The information in your web pages, documents, knowledge repositories or enterprise content management systems (CMS) can quickly and easily be extracted, synthesized and used to train virtual assistants to answer FAQs efficiently and perform tasks.
Drive Involved Conversations
by applying context to FAQs
Engage users by converting boring FAQs into intelligent and personalized conversations. Construct a Knowledge Graph (KG) – a hierarchy with key domain terms, make it more natural by adding context-specific questions and their derivatives, synonyms, and machine learning enabled classes.
by efficient disambiguation
In the real world scenario, users may provide incomplete or ambiguous inputs, which virtual assistants may fail to understand and provide incorrect responses.
Kore.ai’s advanced NLP capability in the form of a Taxonomy based approach and built-in flows help engage the user in a multi-turn conversation to clarify user inputs and identify the right intent.
by marking the critical parts of the content
Leverage the powerful Annotation tool to annotate documents identifying the key sections of the content. Mark them as Header, Heading, Footer, Exclude or even Ignore page. It will help the Knowledge Graph engine to extract content efficiently and process it to deliver optimized results.