Use Case

Generative AI for Omnichannel After-Sales Customer Support

ABSTRACT
A multichannel GenAI assistant enables continuous, personalized, and proactive after-sales service, improving the customer experience and increasing efficiency through intelligent automation.

Where: Italy
Mission
Companies are required to meet increasingly high customer expectations by providing fast, personalized, and always-available after-sales support—without compromising operational efficiency or service quality. The solution’s mission is to transform after-sales into a continuous, high-value experience, enhancing customer satisfaction and loyalty while reducing pressure on customer care teams.
Solution
The solution is based on a Virtual Agent trained on company-specific documentation and customer service processes, integrated with internal and external knowledge bases. Thanks to natural multichannel dialogue capabilities, continuous learning, and proactive and reactive appointment management features, the assistant ensures an always-on, consistent, secure, and personalized end-to-end customer relationship
Actions
A GenAI assistant supports customers after purchase across all major communication channels—chat, phone, email, SMS, and social media—delivering immediate, consistent, and contextualized responses. It can schedule and remind appointments in real time, handle technical requests, and suggest interventions.
Expected results

 

 

 

 

Increased efficiency through automation and proactive request management

 

 

Improved customer satisfaction and post-sales loyalty

Markets
Ecosystems

Impacts

Technologies

To know more
Research Project

TEMA – Accurate Mapping and Forecasting for Emergency Management

Advanced Technologies and Tools for Natural Disaster Management (NDM)

ARIEN: an AI platform to support the fight against illegal drug trafficking

A holistic approach based on artificial intelligence tools for monitoring the production and illegal trafficking of drugs.

Research Project

QLMD: Quantum Computing for an efficient urban logistical ecosystem

Applying Quantum Computing to urban logistics to optimize routes, reduce costs and emissions, improve sustainability, and tackle complex problems with scalable solutions.