Connect Art of Business with Science of Data

The amount of data generated is increasing exponentially owing to the convergence of various technological forces like cloud, social platforms, IoT, mobiles, etc. However, in today’s day and age, leveraging conventional methods of managing, transforming and analyzing the data, that is available both, internally (within the enterprise) and externally (social, image, unstructured, etc), is no longer sufficient. It requires a transformative approach that can be deployed in complex AI pipelines, Master Data Management systems, big data procedures such as Data Lakes, etc where one applies reasoning to learning and delivers knowledge based analytics. Capabilities in Statistical AI, viz.,ML, etc are now table stakes. What we need is more than that – AI Plus or Smart AI, which is leveraging Semantics (Symbolic AI) as well, to drive intelligence by adding a layer of reasoning, over and above, the regular ML techniques.

Business users find it challenging to understand and gain confidence in the predictions machine learning computations deliver. They do not have an integrated decision making system that combines BI, Real Time Alerts and Predictions, with “what-if’s” to take business decisions in right time. They need platforms that host ML models for live scoring and evaluation and integrate knowledge graphs for informed decision making – AI Dashboards. The platforms need to take data from various sources: - Relational, NoSQL, Graph databases and files and streams with various formats such as comma/tab delimited, XML, JSON, semantic RDF triples, etc. And support harmonization of data with disparate schemas to feed AI Pipelines to deliver predictions using machine learning, extracted knowledge using natural language processing for text and unstructured data as well as social, geo spatial and network security analytics using graph analysis. Harnessing deep insights from the data also requires interpreting and analyzing data using subject specific schemas of relationships and meaning (Ontology). Domain ontologies can be loaded into the same platform as just another data set and the runtime enables the ontology to be applied on the source data yielding rich insights along with relationship and context information which otherwise is buried in the data to develop Knowledge Graphs.

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Technical Collaboration with Franz

OAKLAND, Calif. — January 31, 2017 — Franz Inc., an early innovator in Artificial Intelligence (AI) and leading supplier of Semantic Graph Database technology and Lead Semantics, a Big Data Analytics start-up delivering cloud based Advanced Analytics and Data Science, today announced their partnership to deliver Smart-Data Integrated Data Science.

"The integration of Lead Semantics' Hiddime and AllegroGraph delivers new types of analytic outcomes and insights to provide 'Smart Data' for the Enterprise", said Dr. Jans Aasman, CEO, Franz Inc. "AllegroGraph will bring knowledge integration to the Hiddime platform for one of a kind data science capabilities that will deliver unique value for each user."

AllegroGraph’s Technology Featured by Gartner for Driving Business Value in Data -


Emerging Analytics Startups in India


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Lead Semantics, a new generation AI company integrating knowledge bases and machine learning, develops products and services targeting the area of 'Semantics Integrated Data Science’ for both the Enterprise and the Cloud environments. is first of its kind Semantic Cloud-BI tool that enables advanced analytics on the cloud. an 'Interactive Discovery and Exploratory Analytics' tool (IDEA tool) in the cloud, enables end business users with little IT knowledge to deliver routine to sophisticated BI and advanced Analytics with just point and click interactions in the browser.

Their data science teams deliver NLP, Graph, Machine Learning and Semantic Technology projects that also include integration of complex Big Data engineering pipelines feeding into BI Datawarehouses and Smart Data Lakes. Their pedigree and experience uniquely positions them to take advantage of the recent surge in interest in Smart Data to deliver cutting edge data science that enterprises are striving for globally.