PRODUCT BRIEF​THE INSIGHT DATA PLATFORM FOR EXPLAINABLE AI

A Revolutionary Approach Based on Connected Data Science & Graphs

BENEFITS AT A GLANCEOUR EXPERIENCE FOR YOUR DATA

Make better decisions byanalysing ALL available data
connected in one place

Artificial intelligence usually works on unconnected data, but why
not also considering the relationships that exist between thesedata? It works even better!

You can scan your data andautomatically identify
clusters to find patterns ofinterest
Identify high value entities
via easy risk scoring
Graph visualization enables
you to identify hidden
relationships and view large
networks of interconnectedobjects
You can easily analyse yourdata through an Intuitive
Visual Interface
Explainable artificial
intelligence, always Human
Centered Analysis
Minimal setup is required todeploy and operate
Cloud Native by design

Thanks to decades of experience accumulated by LARUS,
Galileo.XAI uses graphs as an input for AI algorithms and is able to
make predictions by capturing feedbacks capable of fueling
improvement processes.
So, this solution overcomes the difficulties that today prevent us
from translating knowledge into action.
In LARUS we know very well how human beings are born to reason
by associations, links and relationships, hence we are sure that onlygraphs are the right representation for complex data analysis atscale.
Galileo.XAI, through Network Science and Graph Visualization,
helps to simplify what is complex, allowing you to discoverbusiness insights in an easy and intuitive way.

INSIGHT DATA PLATFORM
Through sophisticated components of Graph Visualization,
Artificial Intelligence, Natural Language Processing, Big Data
Analytics and Network Science,
Galileo.XAI is able to:

Cloud IT security guaranteedby certifications 27001 \27017
27018 iso\iecCreate analyses and reportsthat can be shared with theteam
Fast response, even withbillions of records
Produce repeatable results:
instantly save and re-run
analyses© 2021 Larus Business Automation. All rights reserved.

Simplify the understandability of big data through graphs.
Enable the business to obtain the information to make better
decisions about its points of weakness and the most pressing
opportunities.
View information in a clear way and highlighting links andrelationships between data.
Making predictions in a human centric way with the help ofexplainable artificial intelligence.

A VISUAL REPRESENTATION OF DATA, IN THE FORM OF
GRAPHS, HELPS US GAIN ACTIONABLE INSIGHTS AND
MAKE BETTER DATA DRIVEN DECISIONS.

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GALILEO.XAI CORES
POWERED BY GRAPHS
Graphs provide a better way of dealing with abstract concepts like relationships and interactions. Theyoffer an intuitive visual way of thinking about these concepts.
Graph Theory is used to study and model Social Networks, Fraud patterns, Power consumption patterns,virality and Influence in Social Media.
From a Computer Science perspective – Graphs offer computational efficiency. The Big O complexity forsome algorithms work better for data arranged in the form of a graph (compared to tabular data).
Traditional databases allow you to see blocks of facts - but if you want to find out how they’reconnected, you need to work harder to perform some analysis. If you’re dealing with a large amount ofdata this can take significant time and effort.
Key benefits of using graph networks for link analysis:
Intuitive and easy to use: Our brains love visualization - over 50% of the brain is involved in visual
processing, so a graph network is inherently easy to understand.
Insightful and powerful: Reveal hidden connections between data to define and assign different
profiles to users or find pattern and use this information to feed AI algorithms and get predictions.
Save time on analysis: Spend less time on manual scanning and analysis to discover and identify
trends, and get an always up-to-date picture of your data.

EXPLAINABLE ARTIFICIAL INTELLIGENCE
Organizations are relying more and more on Artificial Intelligence (AI) and machine learning models.
This leads to increasing attention on the reliability, correctness and ethics of the results: Artificial
Intelligence has to be explainable and above all it must be understandable to end users.
Today most machine learning applications do not allow you to understand the operations and the basisof algorithms, making machine learning a kind of black box.
Explainable Artificial Intelligence (XAI) was born as a direct consequence of the need to give an answer
to this issue, with a set of techniques and approaches useful for understanding, presenting and providing
a transparent view of AI models, thus infusing greater confidence in the algorithms used and giving
important feedbacks for improving results.
For these reasons, among the fundamental characteristics of Galileo.XAI there is the explainability of theAI models results. Because analytics and artificial intelligence should help, but not completely replace,human experience and understanding.

BUSINESS-FRIENDLY INTERFACE
Galileo.XAI is a platform with an interface designed to allow the users to connect with technology.
It is an easy-to-use graph data platform, in fact it requires minimal explanation on its usability even for
non-technical users.
It allows collaboration on analysis creation which helps improve teamwork and time management.
Galileo.XAI is not overly complex, but instead is straightforward, providing quick access to common
features or commands. It has a well-organized front-end, making it easy to locate different tools andoptions.
Galileo.XAI is:

Simple to install
Easy to update
Intuitive© 2021 Larus Business Automation. All rights reserved.

Easy to troubleshootIn line with standards
an effective error handler

Efficient
Pleasant, easy-to-navigate
Easily integrated

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GRAPH DATA CLOSES THE GAP BETWEENHUMANS AND MACHINES

FUNCTIONALITIESGalileo.XAI, nomen omen, follows the modern empirical-experimental scientific method introduced by Galileo
Galilei which provides: the formulation of hypotheses, the deduction of observational consequences of thehypotheses and verification as an empirical control, trying to lead reality to a quantitative mathematical fact likedata-driven decisions.

Business Understanding:Graph Data Science

Business Understanding consists of aprecisespecification of the problem together withevaluation methods on how to achieve the goals.

Graph Data Science is a science-driven approach togain knowledge from the relationships and patterns
in data, typically to power predictions

Galileo.XAI allows the user who has already formulated
a series of hypotheses, to encode them in the system(which will automatically provide the evidence), andthe user who still has to formulate these hypotheses,
to analyse their data through the Discovery and Graph
Data Science sections to formulate them.

Galileo.XAI allows the user to easily build very dynamic
and complex pipelines. Combining network sciencealgorithms, the user can find the most importantnodes, cluster them into meaningful groups, find thebest paths and much more. Graph algorithms have a
proven applicability in many areas. If graphs are thebest way to represent complex systems, graphalgorithms in Galileo.XAI are the Swiss Army knife to
uncover unknown dynamics from them.

Knowledge extraction
Knowledge extraction is the creation of knowledge
from structured and unstructured sources (findanomalies, extracting and discovering patterns andcorrelations)
Galileo.XAI, through the Database section, imports
structured and unstructured data (also using a natural
language structure - NLP -) to build the database thatwill constitute the Knowledge Graph on whichknowledge will be extracted, as well as creating both
BTREE and FULLTEXT indexes to speed-up yourresearches and enhance your filtering

Data Quality
Data quality is a measure of the condition of data
based on factors such as accuracy, completeness,consistency, reliability and whether it's up to date.
The presence of poor data quality is a real businessproblem that negatively affects the effectiveness ofcritical decisions made by companies. To address thisissue, Galileo.XAI offers functionalities of verificationand continuous Improvement of Data Quality.

Data Exploration

Feature Engineering
Feature engineering is the process of using domain
knowledge to extract features (characteristics,properties, attributes) from raw data. Features areused by predictive models and influence results.
Galileo.XAI, through the Discovery section and Graph
Visualization, allows the identification and the buildingof different features that enables the user to trainmodels and configure Machine Learning algorithms.

Predictive Modeling
Predictive modeling is a commonly used statisticaltechnique to predict future behaviour.
Galileo.XAI offers a Predictive Modeling Solution, a formof knowledge extraction technology that works byanalysing historical and current data and by
generating a model to help predict future outcomes. It
may have a great impact on many business scenarios
helping reducing costs or increasing profits.

Data Visualization

Data exploration is the first step of data analysis
used to explore and visualise data to uncoverinsights from the start or identify areas and patterns
to dig more into.

Data visualization is a way of representing
information graphically, highlighting patterns andtrends in data and helping the reader to achieve
quick insights.

Galileo.XAI provides significant statistics and acomplete set of Graph Visualization features that allow
you to investigate the data interactively, also capturing
the temporal dimension, in fact the knowledge Graphs
are rarely static and, as networks, they evolve
dynamically following the connections.

Galileo.XAI allows the user to understand the outputs,
making them explainable and reliable throughsophisticated visual representation techniques. Theseoutputs, once validated, enrich the starting Knowledge
Graph, transforming themselves into new knowledge
useful to make the right business choices.

© 2021 Larus Business Automation. All rights reserved.

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GALILEO.XAI DESIGNGALILEO.XAI IS CONFIGURED AS A PRODUCT BASED ON A MODULAR DESIGN WITH 3 LAYERS,THEREFORE THE AREAS OF USE OF THIS SOLUTION CAN BE CONSIDERED INFINITE, IN THE
MOST VARIED MARKET SEGMENTS.
Galileo XAI foundation is identified as an Insight Data Platform. It uses state-of-the-art graph-relatedtechnologies and it can be extended with:Additional components (mid layer) composable by the users themselves by buying additional
components or modules from the marketplace to benefit from more features.
Apps (top layer) where you have the most common use cases in the form of micro applications,tailored with ad-hoc functionalities. This Apps are totally custom, fully tailored on customer needs;
and built with Structr (low-code approach).

YOUR CHALLENGE, OUR SOLUTION!

Apps
Add-onsFoundation

Business domain experts benefit from the insights generated by the underlying graph-based algorithmsand Explainable Artificial Intelligence with dedicated features, specifically designed for their businesschallenge.
DISCOVER ALL OUR APPS AND FIND THE SOLUTION TO YOUR BUSINESS PROBLEM! YOU CREATE THE
CHALLENGE AND GALILEO.XAI PROVIDES YOU WITH THE SOLUTION.
FRAUD DETECTION
RECOMMENDATIONMASTER DATA MANAGEMENTIDENTITY AND ACCESS MANAGEMENTCUSTOMER ANALYTICS
LIFE SCIENCE
IT ASSET MANAGEMENT
SOCIAL NETWORKS ANALYSISLARUS helps clients to build custom data solutions in order to optimize theirdecision-making process, boost profits and stay competitive.
In LARUS we create your exclusive software for business and we help companies
all over the world by designing big data-driven platforms, based on the mostinnovative open-source technologies, thanks to a solid experience gained indifferent areas: governance, insurance, finance, industry, commercial and telco.
© 2021 Larus Business Automation. All rights reserved.

Do You Have AnyQuestions?
Contact us around the globe:+39 041 50 60 149
info@larus-ba.it

www.galileox.ai

www.larus-ba.it