Development & deployment

Design and development of Artificial Intelligence Solutions

Predictive Analysis

Predictive analytics is the analysis of incoming data to identify problems in advance. As the name suggests, predictive analytics is used to determine the likelihood that certain events or outcomes will occur in the future. Using statistical methods and machine learning algorithms, it is possible to extract knowledge from past and present data and transactions. This allows us to extrapolate models that are able to provide predictions of events and future trends.

AI-inside has extensive know-how in advanced analysis and predictive analysis, which allows us to predict:

  • Machine failures
  • Quality defects
  • Process deviations
  • Performance indicators
  • In addition to a wide range of applications covering maintenance, logistics, engineering etc.

Our predictive analytics solutions, which are decision support tools, enable our customers to proactively respond to prevent inefficiencies in manufacturing operations.

 

Vibration analysis and monitoring

Artificial intelligence provides many powerful techniques for handling large amounts of information on both a particular domain and expert information. This expert information can consist of a wide range of facts, figures, descriptions and other knowledge that an expert normally uses to solve difficult problems. To facilitate the monitoring of mechanical health based on vibrations, we have developed software solutions constituting an intelligent front end for spectral analysis of machine vibration data. This solution makes it possible to constantly monitor the state of a device and to alert if there is a bad vibratory trend. Thus, our customer will avoid an unexpected stop of his equipment and will be able to set up preventive actions.

Automatic recognition of photos and objects, computer vision

Automatic detection of a specific object by visual inspection is a task involved in multiple industry processes, such as sorting, inventory management, machining, quality management, packaging, etc. . Until now, the quality control part of the manufacturing cycle remains a difficult task as it is based on the visual competence of each individual and the working conditions and environment. With Artificial Intelligence, most of these complications can be treated. AI-inside develops solutions based on deep learning and automatic detection of objects, making it possible to distinguish good parts from defective parts on an assembly line with incredible speed. This gives our customers enough time to take corrective action. This is a very useful solution for dynamic environments where product lines are constantly changing. In addition to quality control, our know-how in industrial vision is spread over other specific applications at the request of our customers.

 

RPA (Robotic Process Automation)

Robotic Process Automation (RPA) is the technology that today allows anyone to configure software, or a "computer robot", to emulate and integrate the actions of an human interacting within digital systems to execute a business process. RPA robots use the user interface to capture data and manipulate applications as humans do. They interpret, trigger responses and communicate with other systems to perform a wide variety of repetitive tasks. Also, an RPA software robot never sleeps, makes no mistake and costs far less than an employee. On average, an employee spends more than 30% of his time interacting with different applications of the information system. The collaborator is often required to perform many re-entries or copy-and-paste data from one window to another, or to compare and verify information from two applications and many other repetitive manipulations. AI-inside develops RPA-type solutions, which consist of implementing "software robots" to automate these tedious tasks with no added value.