Industrial Intelligence

Advanced analytics is the key to unlocking the hidden potential in your data. This approach, which is based on mathematical and statistical techniques, makes it possible to extract complex patterns and predict future behaviors, in order to optimize business decisions, processes and strategies.

Meti is our causal inference platform that digitizes the knowledge of experienced practitioners, making it available to new users.

Advanced analytics

Advanced analytics concerns it self with developing tailor-made solutions that make the most of statistical methods to reveal latent information and correlations in data. By transforming massive amounts of data into clear insights, you can make data-driven decisions, increase process effectiveness, and reduce the risk of making costly errors.

Predictive maintenance

Predictive maintenance uses data and analytics to estimate when equipment or machinery is going to need maintenance. By constantly analyzing operating conditions, you can identify early signs of impending failures, enabling preventative action before problems actually occur – an approach that reduces downtime, optimizes resources, and extends the useful life of assets.

Decision Support Systems (DSS)

Decision support systems are tools that analyze cause-and-effect relationships between variables to lead to transparent and informed decisions. Causal approaches allow you to understand the potential impacts of decisions before they are made: in essence, they offer advanced aid in the decision-making process, by considering not only the data, but also the underlying dynamics.

RPA

Robotic Process Automation (RPA) is a technology that uses software to perform repetitive tasks automatically. This technology provides operational efficiency, reduces human error, and allows people to focus on more creative and complex tasks. RPA is mostly used in fields such as administration and finance, human resources, and logistics.

Modeling & Control

A modeling and control system is a designed to improve process performance and stability. The modeling phase involves creating a mathematical model that provides an abstract and quantitative representation of the relationships between variables. The control phase involves the implementation of algorithms to influence the system in a way that keeps process variables within certain limits.

Energy & Process Optimization

Economic and environmental sustainability also depends on the efficient use of resources. Optimization algorithms and intelligent agents can help reduce energy waste by effectively controlling plants, recover production times thanks to continuous scheduling and avoid waste cause by inefficiencies in the process.

A multidisciplinary team

Industrial Intelligence projects are handled by multidisciplinary teams, combining the different skills needed to tackle complex challenges. By involving experts in machine learning, software developers, UI/UX designers, domain specialists, psychologists, cybersecurity experts, a holistic perspective is obtained, able to ensure the balanced development of the project and to preserve the quality of the implemented solutions.

Human beings reason by cause and effect: they tend to look for logical connections between events, attributing a cause to each situation and observing the effects that derive from it. Through sophisticated mathematical and statistical tools, AISent has built algorithms that reproduce this cognitive process: METI is the causal inference platform that digitizes industrial knowledge and revolutionizes troubleshooting, tracing malfunctions, errors and defects back to specific causes.

Via Pascoli 14 - 24020 - Gorle, Bergamo - Italy

VAT IT04287240164

Share capital 40.000,00 euros

info@aisent.io

Via Pascoli 14 - 24020 - Gorle, Bergamo - Italy

VAT IT04287240164

Share capital 40.000,00 euros

info@aisent.io