What is an insight engine?
An insight engine combines search with AI to deliver actionable insights derived from the full spectrum of content and data sources. Whether they are internal or external. It also extracts valuable information from large volumes of complex, diverse data sources, extracts name entities: name of people, name of companies, dates. etc…to provide deeper insights to users so they can make better decisions and discover knowledge.
Engine insights, the future of shared knowledge
As data grows, insight-driven enterprises need to reinvent their data supply chains to stay agile and create competitive advantages. Harnessing the power of unstructured data (documents, images, emails, media, etc.) is vital to this process. But as 80% of all data is unstructured, this is not an easy task.
And insight engine provides contextually relevant information. Finding relevant knowledge across all available data requires cognitive systems that use natural language processing (NLP). It understands unstructured data from texts (e.g., documents, social media blogs, engineering reports, market research) and rich-media content (e.g., videos, scans). Machine-learning algorithms help refine the insights gained from data.
Trade and company dictionaries and ontologies help discover synonyms and relationships between different terms and concepts. That means there’s a lot of intelligence and horsepower under the hood of a system providing relevant knowledge or insight.
It leverages machine-learning capabilities to continuously improve the relevancy of search results. Machine-learning algorithms (e.g., collaborative filtering and recommendations, clusterization, similarity calculations for unstructured contents, and predictive analyses) provide added value by continuously refining and enhancing search results to provide the best relevancy to users.