A key capability for any cognitive being is the provision to capture, filter, analyze and process data from its surrounding environment. Much like the human primitive brain, Element Sensory Hub is tasked with gathering information, interpreting it, and constantly alert to the needs of basic needs.
The Hub can ingest any structuredor unstructured data, regardless of format, volume, velocity or method of acquisition. Data may be collected from any internal repositories, open sources, deep web locations,high credential data sources or any other information source relevant to the organization.
The Sensory Hub is fully automatic, and is focused on immediate processing of Data In Motion. It includes ingesting raw data arriving from a multitude of sources, normalizing it, persisting it, and applying policies where immediate action is required.
At the heart of this Hub is Element's robust Data Science, Orchestration and Integration framework. Our framework is a leading data-driven innovation, helping our customers to discover the potential hidden in their data which residing either internally OR externally, mine for fresh insights, or predict new futures. Our cognitive grade, framework is fast to deploy, easy to scale and intuitive to learn.
Enabeling the connectivity and seamless integration to any data or data source, with 10s of domain specific modules, hundreds of ready-to-run examples, a comprehensive range of Text Analysis and Machine Learning tools, and the widest choice of advanced algorithms available, is the ultimate way to bring your data to live
The main consumer of the integration framework is Blackswan's search engine. This engine is supported by cutting edge technologies working jointly to create the most sophisticated yet simple to use search and retrieve service.
Element Search engine is supported by our proprietary Machine Learning training platform that assist the search engine to fetch better more accurate results. The Machine Learning platform is enabling our customers execute specific ontological search facilities.
In order to make sense of what we are collecting we are running a set of text analysis algorithms to classify data and extract relevant facts from it We are able to detect entities and relations, understand that entities and relations are forming an event. And assess the validity or risk OR an opportunity of a given event
Relevance based ranking is the core functionality of a search engine. Our search engines employ ranking algorithms which are assigning a configurable relevance scores to the documents based on the domain specifics.
We are heavily employing Machine Learning algorithm to calculate ranks of the web documents we are collecting. So that the most relevant documents are popping to the top.
'Element' is facilitating multiple vertical search engines that are performing a surgical most accurate ontology led search.
Differently from many other search engines, Element search engine is not based on simple keywords but on actual the meaning of the words themselves the context. This is being achieved due to Blackswan years of investment in Natural Language Processing (NLP) enhanced by Artificial Neural Network (ANN).
The ability to truly democratize the process is perhaps the most important element of any enterprise machine learning platform. Element automates the entire modeling lifecycle, enabling users to quickly and easily build highly accurate predictive models.