AI & ML:
HOW TO USE THEM

Artificial Intelligence & Machine Learning
are transforming business

But even as the technology advances, companies still struggle to take advantage of it, largely because they don’t understand how to strategically implement Machine Learning solutions in service of business goals.
Machine Learning algorithms are often categorized as being supervised or unsupervised. Supervised algorithms require humans to provide both input and desired output, in addition to furnishing feedback about the accuracy of predictions during training. Once training is complete, the algorithm will apply what was learned to new data. Unsupervised algorithms do not need to be trained with desired outcome data. Instead, they use an iterative approach called deep learning to review data and arrive at conclusions. Unsupervised learning algorithms are used for more complex processing tasks than supervised learning systems.

REPLY NETWORK OF HIGHLY SPECIALISED COMPANIES OFFERS TODAY ARTIFICIAL INTELLIGENCE AND MACHINE LEARNING SOLUTIONS FOCUSED ON TWO MAIN DRIVERS


innovative
technology

Algorithms and AI techniques are used to solve the interaction between humans and machines and to make machines understanding more easily human data.

REPLY COMBINES DEEP TECHNOLOGY KNOW-HOW WITH INNOVATIVE STRATEGIES AND FUNCTIONAL EXPERTISE TO EMPOWER MACHINE-HUMAN INTERACTION!

enterprise
domain

Artificial Intelligence is used to improve or automate processes of an enterprise in order to improve revenue or reduce costs or to completely redefine products.

REPLY PROVIDES AI SOLUTIONS THAT RELY ON ALL THE INFORMATION POSSIBLE TO MAKE BETTER CHOICES, INCREASE AGILITY, CONSISTENCY AND PRECISION!

Reply Framework

Hot Spot

Robotics for Customers is here!

Reply has built its own Robotics for Customers approach in the context of Data-Driven Customer Engagement. Robotics for Customers is a framework built on two foundational pillars: Recommendation Systems and Conversational Systems.

Robotics for Customers is here! 0

Data Robotics Accelerator

Automated Invoice

Automated Invoice is the solution, also available as a service, which facilitates the automated management of the accounts payable process, from the posting phase to the reconciliation between invoices and purchase orders/delivery notes/receipts, highlighting the differences identified.

Data Robotics Accelerator

Brick Machine Learning

Brick Machine Learning is the solution that makes it possible to simulate various configurations used in automated production lines, in order to recommend the optimal mix of devices required to achieve the overall performance requested by the end customer.

Data Robotics Accelerator

Customer Recovery

Customer Recovery is the solution that faces the challenge of behavioral approach on credit risk management. The solution is developed on Microsoft Azure Machine Learning, the service that allows building and testing powerful cloud-based predictive analytics.

Data Robotics Accelerator

Employee Monthly Expenses

Employee Monthly Expenses is the solution that facilitates the automated creation of expense reports starting from the underlying cost items, quickly and without the need for manual intervention.

Data Robotics Accelerator

Know Your Orders

Know your Orders is the solution that makes it possible to create a simple interface which can be consulted by users using a natural language, thus facilitating access to information while ensuring consistency and accuracy.

Data Robotics Accelerator

Match-up

Match-up is an advanced tool for the analysis, reconciliation and matching of complex data (single and/or multiple). The use of this tool finds application in data-related processes.

Artificial Intelligence & Machine Learning

Hot Spot

Artificial Intelligence & Machine Learning: Reply Offering

The convergence of Big Data with Artificial Intelligence has emerged as the single most important development that is shaping the future of how firms drive business value from their data and analytics capabilities.

But even as the technology advances, companies still struggle to take advantage of it, largely because they don’t understand how to strategically implement Machine Learning in service of business goals.

Artificial Intelligence & Machine Learning Reply Offering 0