Larus on the wave of Graph Thinking

Data analysis is now a fundamental and consolidated aspect not only to guide the strategic decisions of companies, but also to gain competitive advantages. It becomes crucial to generate new knowledge from data through the analysis of connections, the relationships between information.

Redefining and understanding a problem in terms of interconnections is the basis of graph thinking, a natural and intuitive approach to represent complexity, unlike the common “rows and columns” representation, which is an unnatural way of representing data for a human being.

Graph thinking, therefore, improves the ability to make data driven decisions, but also requires a change of mentality, a new approach to understand, deploy and apply technologies that are able to take advantage of graphs and link analysis.

Thanks to our focus on innovation and the ability to attract talents, since our establishment in 2004 we at LARUS Business Automation have recognized the value of these tools and have become a leader in Italy for graph technologies and connected data science.

As the only Italian company premier partner of Neo4j, a database that stores and manages data in their most natural and connected state, we have focused on the development of Insight Data Platform that make Network Data Science their strong point.

Galileo.XAI, a solution Larus launched in 2021, is a clear example of how working with a graph database is optimally suitable for the analysis of data in different market segments and for a wide variety of use cases: from fraud detection to customer analytics, to supply chain.

It is a flexible and fully integrable product that, thanks to sophisticated components of Graph Visualization, Artificial Intelligence, Natural Language Processing, Big Data Analytics and Network Science, is able to allow companies to obtain the insights they need to make targeted decisions and visualize information by highlighting the links between the data. Finally, Galileo.XAI allows companies to make predictions in a human centric way thanks to Deep Tensor, an explicable artificial intelligence engine born from Larus’ collaboration with Fujitsu.

Larus therefore also transforms machine learning, incorporating graph-based functionality into traditional machine learning pipelines and ensuring that its innovation does not end with network science, but uses it to take the whole data processing method to a new level.

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