Applies near-human logic and reasoning to assist research and decisions ! Truly understands complex queries, leverages semantic information and then answers in natural language.
A truly cognitive assistant must have two essential components – the ability to process unstructured information into semantic form (NLU), and to give a user cognitive access, via natural language query (NLQ), to this information. Deep understanding is required using knowledge-based AI, not just intent determination or statistical language analysis.View Demo
The solution develops an interactive semantic representation of business events on a timeline.
It applies entity extraction, pronoun replacement, inferencing and knowledge-references to Understand incoming unstructured information and merges it with available structured information
An analyst can now interact with information synthesized across time and topics of interest
An analysis relies on the ability to establish relationships and possible reasons for an occurrence.
The solution Understands context and meaning of incoming unstructured information, and stores it appropriately.
The result is an ability to explore causal relationships via complex questions.
Deep insights based on semantic understanding, lead to granular insights and lower risk