Leveraging Unstructured Data for Improved Investment Strategies @BigDataExpo #AI #BigData #FinTech

The next BriefingsDirect Voice of the Customer digital transformation case study highlights how high-performing big-data analysis powers an innovative artificial intelligence (AI)-based investment opportunity and evaluation tool. We'll learn how LogitBot in New York identifies, manages, and contextually categorizes truly massive and diverse data sources. By leveraging entity recognition APIs, LogitBot not only provides investment evaluations from across these data sets, it delivers the analysis as natural-language information directly into spreadsheets as the delivery endpoint. This is a prime example of how complex cloud-to core-to edge processes and benefits can be managed and exploited using the most responsive big-data APIs and services. To describe how a virtual assistant for targeting investment opportunities is being supported by cloud-based big-data services, we're joined by Mutisya Ndunda, Founder and CEO of LogitBot and Michael Bishop, CTO of LogicBot, in New York. The discussion is moderated by BriefingsDirect's Dana Gardner, Principal Analyst at Interarbor Solutions. Gardner: Let's look at some of the trends driving your need to do what you're doing with AI and bots, bringing together data, and then delivering it in the format that people want most. Ndunda: LogitBot is all about trying to eliminate friction between people who have very high-value jobs and some of the more mundane things that could be automated by AI. Today, in finance, the industry, in general, searches for investment opportunities using techniques that have been around for over 30 years.