Keyword

Artificial Intelligence & Machine Learning

Artificial Intelligence & Cloud

Master

Artificial Intelligence & Cloud - Master Hands-on Innovation

It is a unique programme, recognized by MIUR (Ministry of Education, University and Research) and developed in collaboration with Politecnico di Torino, to offer a professional specialization in the most innovative fields of the IT sector. The first edition of the Master’s programme on Artificial Intelligence and Cloud is scheduled to start in January 2021 and a maximum of 40 students will be admitted.

Artificial Intelligence & Cloud - Master
Hands-on Innovation 0

Best Practice

Automated help Desk

Cluster Reply Automation Intelligence practice has skill, training and experience with Hyper-automation technologies, including conversational interfaces, cognitive services and Robotic Process Automation. Cluster Reply can tailor the conversational interface solution to fulfill different customer needs, assisting during the entire solution lifecycle, from planning to design, implementation and support and making sure they choose the correct approach to enable success.

17.06.2020 / Fully Digital

Event

Aws Summit Online 2020

Join the AWS Summit 2020 the new fully Online Edition. Hear about the latest trends in cloud during the Opening Keynote of Werner Vogels, CTO by Amazon.com, and dive deep in 55 breakout sessions across 11 track. Meet REPLY at the Virtual Booth and discover the latest expertise on AWS Technology about: Machine Learning & Artificial Intelligence, Big Data, IoT and Industrial Software.

Voice Interaction

Brochure

Voice Interaction Gets Contextual

Voice experiences are radically changing the way we interact with technology. Connect Reply joins the physical and digital world, crafting amazing IoT technology. Connect Reply is experiencing the true beginning of the Internet of Things era, in which the physical and digital world talk to each other and empower people and businesses.

Voice Interaction Gets Contextual 0

31.10.2019 / Milan

Fundamentals of Deep Learning for Computer Vision

Machine Learning Reply is the Reply Group’s specialist in the development of artificial intelligence solutions. On 31st of October, as a Preferred Partner of Nvidia, a training session will be held which will be aimed at deepening the Deep Learning techniques for Computer Vision.

Fundamentals of Deep Learning for Computer Vision 0

AI for Retail

Best Practice

AI Store Check: Shelf Survey at POS with just one click

"AI Store check" is an application which allows sales representatives to automatically perform shelf surveys – all they need to do is create photos of the shelves with the app and upload them to the cloud. An AI is then used to perform an analysis.

Quantum Computing

Best Practice

Quantum & Accelerated Computing

Reply is exploring the potential for quantum computers and quantum algorithms to identify solutions to previously insoluble problems.

As it researches and explores quantum computing, Reply is developing solutions to use cases of interest to its customers.

DISCOVER MORE!

Quantum & Accelerated Computing  0

AUTOMATION

Best Practice

CHALLENGES FACED IN THE INDUSTRY OF MASS PROCESS AUTOMATION

The challenge has been and remains the skill of determining what to automate, how to automate it and most importantly when to give up, to produce a pipeline of automation. Find out about the challenges of process automation.

Automotive

Product

The Sitecore Experience platform for the automotive sector

Cluster Reply has exploited the innovative characteristics of connected devices to create a solution for enhancing customer experience in the automotive sector. The solution is based on the integration of the Sitecore Experience platform with Microsoft Azure Cloud services.

22.05.2018 / Milan

Event

ExplAIn your tomorrow today

Technology Reply, in collaboration with Oracle and other partners, participates in the Explain Your Tomorrow Today, an event dedicated to the innovative technologies of AI, Machine Learning and Analytics.

Artificial Intelligence & Machine Learning

Best Practice

AI & ML: How to use them

Intelligence and Machine Learning are strategically important for driving enterprise strategies.

With Reply you can discover how Artificial Intelligence can support some important business needs and how strategically implement Machine Learning in service of business goals.

AI & ML How to use them 0

Recognition

Case Study

NATURAL LANGUAGE PROCESSING ACROSS THE AUTOMOTIVE VALUE CHAIN

Reply supported a big German automaker with millions of enquiries about their products.

Data Reply developed a multi-threaded text analytics service that takes the stream of text documents, applies NLP methods to retrieve significant entities and keywords, clusters the documents hierarchically and generates intuitive labels.

Prediction & Prescription

Case Study

INSURANCE FRAUD DETECTION

Reply supported a large insurance company to identify potential fraudulent users.

Data Reply developed an unsupervised anomaly detection engine to separate fraudulent users from honest ones, so that no righteous person would be suspected to be guilty of an offence.

Prediction & Prescription

Case Study

MACHINE LEARNING FOR FRAUD FIGHTING

Reply supported one of the first Consumer Credit Company in Italy with millions of loans every year.

Target Reply‘s solution anticipates and automates fraud detection. It identifies serial fraudsters that change their habits to evade controls and creates more advanced and predictive models that fit in new and unknown contexts.

Artificial Intelligence & Machine Learning

Hot Spot

Intelligence

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.

Intelligence 0

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

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.

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

Artificial Intelligence

Best Practice

Towards Augmented Intelligence

Artificial Intelligence and Augmented Intelligence have entered the business realm, been the subject of academic and online discussions and captured the collective imagination with great enthusiasm. Target Reply explains how Artificial and Augmented Intelligence can bring increased value to customers in different areas of application, showing the techniques and technologies applied to real use cases.

The Banca Mediolanum case Data Analytics Laboratory and implementation of a Recommendation Engine  0

Financial Services

Case Study

The Banca Mediolanum case: Data Analytics Laboratory and implementation of a Recommendation Engine

With the aim of experimenting with an Advanced Analytics approach, the Data Analytics laboratory initiative launched by Banca Mediolanum involves a partnership between the Marketing Research team and Reply for the development of advanced data analysis mechanisms and the design of proactive services, tailored to the customer’s needs.

Using Deep Learning and Knowledge Graphs to anticipate customers’ needs 0

Recommendation Systems

Best Practice

Using Deep Learning and Knowledge Graphs to anticipate customers’ needs

There is no mystery behind traditional collaborative algorithms: they simply try to suggest similar content to what we have previously watched, or what other users with similar tastes to us have been watching. Yet we can go even further using Deep Learning and Knowledge Graph methods that leverage contextual and unstructured data.

Recommendation Systems

Best Practice

Reply's approach and methodology for bringing recommendations in production environments

Reply has developed the framework Robotics for Customers which allows customers to build a time-to-value Recommendation System that can be easily integrated into any existing platform.