High Tech on the Low hosted by Jordan Kastrinsky, is on a mission to make high tech accessible to the world. In my podcast, I explore the many different facets of the world of high tech from development to marketing, to sales, to entrepreneurship and more! With society turning ever more towards technological solutions to make processes more efficient and secure, it is important, now more than ever, that we unite the high-tech sector's collective resources under one roof to reap the benefits of this knowledge-sharing. There is so much opportunity out there to grow within the industry that we must provide the tools through which to do so.
The no-code revolution, as experts have termed it, is quite the breakthrough for the tech industry. Over the years, entrepreneurs and companies have come to the realization that there exists a major barrier when it comes to technological development due to the technical abilities required of those involved in the actual development process. Moreover, development is not an easy process and can often drain organizations of both needed resources and time. As part of overcoming these challenges, no-code allows programmers and non-programmers alike to create new applications or programs using graphical user interfaces and configuration instead of traditional computer programming.
But how does this apply to artificial intelligence? "For businesses, translating the loads of data they have into meaningful insights is key," says Assaf Egozi, CEO and co-Founder of Noogata. As many readers may be familiar with, artificial intelligence uses various models fed by massive data sets to predict trends, results, and other insights. Many businesses today are employing artificial intelligence solutions as a means of gaining better control of their business data and applying it accordingly.
To gain this needed data understanding, organizations are turning to many different solutions including automated machine learning and others. Yet, even with other automatic modelling platforms, there remains a major burden on data teams within businesses. "Our intention was to help organizations get more leverage on those teams, those teams are choked as it is," Assaf adds.
By using a top-down approach he learned during his time as a consultant at McKinsey for the companies he is now helping today, Assaf suggests that Noogata is built to assist businesses and organizations assess the problem they truly want to evaluate. Often for companies understanding their main question can be a challenge since data that is improperly managed can be overwhelming. Often, however, these issues are shared across the board which is the strength of the Noogata solution. "The 3 factors that make Noogata work are that we see common problems and data sets and take into account different needs of how to apply the solutions," remarks Assaf. This type of approach places Noogata above many solutions as Assaf claims to not only aggregate data but provide analysis based on each organization's individual needs.
The key critical element in Noogata however lies beyond its technological feat. It lies in the fact that Assaf used his prior consultant experience, not to mention his computer science expertise, to address a need. The need: a better way to manage AI data insights and conduct data analysis for businesses, one that reduces costs and resources.
Is it succeeding? All signs point to the affirmative!
