On the verge of the next digital revolution, we have made AI and Machine Learning our core business. Over the years we have developed extremely vertical skills that allowed us to create tools currently used by Fortune 500 companies for analyzing and visualizing big data from social and mass media.
AI is often regarded as something extremely complex and nebulous, yet AI it’s nothing but the ability of a computer program to think and learn on its own. Below you can see how we implement machine learning on big data.
AI has revolutionized the way in which we build applications and get insights from data. We’ve developed a set of models that can be used to create better processes, launch new web services and obtain a competitive advantage.
Text analysis is a domain of study that deals with transforming large unstructured text data into understandable insights. In order to do that it splits documents into tokens and then understands each token’s role and meaning within the context.
Machine learning is divided into three categories: supervised learning, unsupervised learning, and semi-supervised learning.
AI can help users at all stages of the big data cycle: from collection to storage to retrieval to aggregated visualization. Crucial measures for identifying patterns, making decisions, and anticipating events.
AI has been around for a while but nowadays computing power, data availability and new algorithms have led to major breakthroughs. Let's see where we can help you:
Users create an immense amount of data through social media interactions. We can use Machine Learning to analyze this data and make sense of it.
AI is responsible for most increases in conversion rate with applications such as product recommendations or chatbots. ML can be used to predict optimal stock levels and price points.
Whether the data comes from factory machines or from chips installed into trees, AI can manage, analyze and create meaningful insights with the data, which means predicting when a machine will break or a tree will fall.
Traditional BI tools require analysts' heavy data manipulation. We believe that the future of BI will be an AI-powered system that ends manual processes and allows focusing on the strategy.
Pulsar is fast growing audience intelligence company based in London. We have developed Pulsar's technologies that enable organizations to understand and draw insight from online conversations across a fast-evolving set of global social media platforms, traditional media and data sources.
Pnat is a University of Florence's spin-off company. Pnat hired Extendi to develop a IoT Dashboard that gathers data from chips installed into trees, store the data in cloud and perform predictive analysis on it.