Data Integration Platform - Your company has lots of data in disparate formats in different locations and also on the web that need to be consolidated for analysis.  Working with all of this data to produce meaningful information is not easy.  We offer a scalable Data Integration Platform and tools to solve this problem.  Our Platform makes it easy to find, clean, consolidate, analyze, and report data arming the user with the solution to make sense of their data.

Analytic Engine - By leveraging new internet technologies, we have developed new analytic tool that is different from other market offers in the area.

Media Management Tools – Istari offers a new class of intelligent media systems. These systems are able to automatically create illustrations for scientific experiments, medical books, architecture projects and more. They will be required in the education process and in art studios. The project is in the stealth mode, please; contact us to be one of the first to implement and to gain competitive advantage.

Intelligent Agents – There are multiple perspectives in using multi-agent systems. Istari involves in various projects, including machine learning,  intelligent user interfaces, and cognitive science.

Machine Reading through the semantic web -The majority of human knowledge is encoded in text. Much of this text is available in machine processable form on the web. But to machines, the knowledge encoded in the texts they read remains inaccessible. They process human texts but do not understand them. With the emerging semantic web significant progress has been made in machine reading, learning and knowledge acquisition. Istari’s research effort focuses on machine learning through the semantic web.

Machine Reading through NLP – The traditional machine processing of natural language (NLP) has improved in the last few years because of progress in  morphological analysis,  name recognition, and  logical form extraction. Still, computers today are not yet able to generate semantic representations on a scale sufficient enough to support automatic knowledge acquisition. The goal of Istari’s research is to make texts semantically processable by machines and to create an advanced machine-learning process.

Architecture and Experimental Design for Real-World Systems – As more artificial intelligence (AI) research is implemented in real-world data management software, the proper design of such systems itself is critical and can be challenging. Our research helps to evaluate different aspects of system and interface architecture& design.

Social semantic web 2.0 and web 3.0 – The social web and the semantic web are related and complement each other. However the levels of sophistication are very different in user-submitted content and in the content with embedded semantics. In the case of semantic web, metadata are embedded and logic-backed. In the case of user tagging, there is just basic metadata. Because of this difference, there are still only limited ways for users to find, customize and reuse data between two webs. As a result, semantic web applications are still of limited use and impact. Istari is working on a new generation of applications that combine the strengths of these two approaches.

Web Interface for Analysis, Science Works and Search Illustrations

“Big data” paradigm and advanced data integration make it possible to get insight into petabytes of data, analyzing the data “on-the-fly” over the web.  But – the results of such a large scale analysis often come in the form of visual interfaces without overwhelming the user. Istari’s cloud-based visualization service provides our clients with visual interfaces  for analyzing and sharing of data resources obtained through the web search or otherwise.

Every day we produce and store more and more data.  The biggest challenge of the petabyte age is not anymore about storing all that data, it is about how to make sense of it.  Istari offers a service  of visually representing complex data sets to make possible analyze data on the fly.  This new web service interface is ideal for visualizing massive amounts of science & search data across the various  domains from life-science to consumer search.

Human  brand and eyes have have a natural limit.  At Istari, we are in business to help a person to make sense of large data massive that is not impossible naturally due to those limits.  We create visual interactive data-representations customized for the particular client case and train them on big sets.  The visual interfaces we offer are various from the trees and tag cloud to the complex interactive maps that a client needs in the cases when the only way to understand a big data set is through visualization.