We use essential cookies and similar tools that are necessary to provide our site and services. We use performance cookies to collect anonymous statistics, so we can understand how customers use our site and make improvements. Essential cookies cannot be deactivated, but you can choose “Customize” or “Decline” to decline performance cookies.
If you agree, AWS and approved third parties will also use cookies to provide useful site features, remember your preferences, and display relevant content, including relevant advertising. To accept or decline all non-essential cookies, choose “Accept” or “Decline.” To make more detailed choices, choose “Customize.”
Customize cookie preferences
We use cookies and similar tools (collectively, "cookies") for the following purposes.
Essential
Essential cookies are necessary to provide our site and services and cannot be deactivated. They are usually set in response to your actions on the site, such as setting your privacy preferences, signing in, or filling in forms.
Performance
Performance cookies provide anonymous statistics about how customers navigate our site so we can improve site experience and performance. Approved third parties may perform analytics on our behalf, but they cannot use the data for their own purposes.
Allowed
Functional
Functional cookies help us provide useful site features, remember your preferences, and display relevant content. Approved third parties may set these cookies to provide certain site features. If you do not allow these cookies, then some or all of these services may not function properly.
Allowed
Advertising
Advertising cookies may be set through our site by us or our advertising partners and help us deliver relevant marketing content. If you do not allow these cookies, you will experience less relevant advertising.
Allowed
Blocking some types of cookies may impact your experience of our sites. You may review and change your choices at any time by selecting Cookie preferences in the footer of this site. We and selected third-parties use cookies or similar technologies as specified in the AWS Cookie Notice.
Your privacy choices
We display ads relevant to your interests on AWS sites and on other properties, including cross-context behavioral advertising. Cross-context behavioral advertising uses data from one site or app to advertise to you on a different company’s site or app.
To not allow AWS cross-context behavioral advertising based on cookies or similar technologies, select “Don't allow” and “Save privacy choices” below, or visit an AWS site with a legally-recognized decline signal enabled, such as the Global Privacy Control. If you delete your cookies or visit this site from a different browser or device, you will need to make your selection again. For more information about cookies and how we use them, please read our AWS Cookie Notice.
Dieser Inhalt steht in der ausgewählten Sprache nicht zur Verfügung. Wir arbeiten beständig daran, unsere Inhalte auch in der ausgewählten Sprache zur Verfügung zu stellen. Vielen Dank für Ihre Geduld.
RSI Drives Digital Transformation on AWS, Putting Users at the Center
“As a public service broadcaster, you have to be really close to the people that you trust with it. This is why I prefer to use AWS. I never had any doubt about using AWS.”
—Massimiliano Babbucci, Head of Digital Innovation, RSI
Digital transformation continues to reshape the media landscape, demanding constant evolution from even the most established players. With a legacy dating back to 1931,
Swiss Broadcasting Corporation has a long history of innovation and is taking its latest stride toward future readiness on Amazon Web Services (AWS).
Radiotelevisione Svizzera (RSI), Swiss Broadcasting Corporation’s Italian-speaking business unit, is developing a new all-in-one mobile app. This venture, powered by artificial intelligence (AI) and machine learning (ML) technologies on AWS, caters to users’ demand for more personalized and dynamic media experiences.
Unifying Digital Content Channels on AWS
Swiss Broadcasting Corporation is a Swiss public broadcasting organization and one of the largest media houses in Switzerland. Serving Italian speakers, its RSI business unit delivered news, sports, cultural, and entertainment content through three disparate apps and a website. To enhance the user experience, the company wanted to combine its digital offerings into a single app so that viewers could access their desired content when and where they wanted it.
“Our idea was to develop an all-in-one application that can collect all of the content that we generate every day,” says Massimiliano Babbucci, head of digital innovation at RSI. “To accomplish this efficiently, we wanted to incorporate AI/ML to automate several parts of our workflow, from collecting metadata to recommending content and personalizing the user’s feed.”
To bring this vision to life, RSI turned to
Claranet Switzerland (Claranet), an
AWS Premier Partner that offers adaptive, scalable technology solutions in the cloud. Having worked with Claranet since 2019, RSI knew that the company held deep expertise in AWS services that it could draw upon to build the new app. When it came to building a large language model using AWS AI/ML technology, however, the project required additional expertise. To deepen and expand this collaboration, RSI also began to work with researchers and students at the Institute of Information Systems and Networking (ISIN), a research institute within the Department of Innovative Technologies at the
University of Applied Sciences and Arts of Southern Switzerland (SUPSI), which is based in Lugano.
“We established a technological hub between RSI, Claranet, and the university,” says Babbucci. “In a very short time, we were able to begin to develop the app with experienced data scientists without the need to train new people. ISIN is in charge of research and defining the best models to use, and then it provides the prototypes to Claranet to standardize and put into production.”
Incorporating AI and ML to Create an All-in-One App
The RSI mobile app is a large language model that incorporates AI/ML technologies that help extract metadata and recommend relevant information to users. For example, ISIN adopted Amazon Comprehend—a natural-language processing service that uses ML to uncover valuable insights and connections in text—to extract relevant language, classify content, and personalize user feeds. Many of these models run on Amazon SageMaker, a service that is used to build, train, and deploy ML models for any use case.
“ISIN researchers first identified some viable models that they can use out of the box,” says Piero Bozzolo, AWS solutions architect at Claranet. “Then, they developed some models from scratch and discovered how to integrate them with Amazon SageMaker.”
The app is hosted on managed AWS serverless services, including
AWS Lambda, a serverless, event-driven compute service. RSI also has the option to use
Amazon SageMaker Serverless Inference—a purpose-built inference option that lets developers deploy and scale ML models without configuring or managing the underlying infrastructure—as needed.
“Currently, 90–95 percent of the infrastructure is serverless,” says Bozzolo. “One thing that I appreciate about Amazon SageMaker is that you can change the whole infrastructure base; you can switch from serverless and provision without much effort.”
RSI has realized several advantages by using this flexible infrastructure. “Using a serverless-first approach on AWS, RSI can scale up to reach millions of customers at any time,” says Bozzolo. “They can do this without worrying about the cost or performance of the application; they can maintain the same level of performance whether they have two concurrent users or 2 million.” Moreover, because RSI’s development team no longer needs to worry about hardware maintenance, they can focus on services and innovation rather than on low-level technical details.
The people involved in this project have enjoyed many benefits as well. Students at the Department of Innovative Technologies of SUPSI had the opportunity to gain practical experience by working on this real-world project. This hands-on experience, including meeting production deadlines and dealing with real-world challenges, provides valuable learning experiences that go beyond traditional university projects. Additionally, RSI journalists benefit from better tools and improved searchability. The automated metadata extraction engine has enhanced the quality of its tagging systems, which helps journalists quickly search for and find the content that they need when they need it.
Building a Foundation for Omnichannel Engagement
The development of the RSI app is still ongoing, and several key features remain on the company’s road map. Over the next 2 years, RSI will focus on adding these new elements and turning the concept of omnichannel engagement into a reality. The collaboration between RSI, Claranet, and ISIN will serve as a robust foundation for these future enhancements.
“As a public service broadcaster, when you have to do a project, especially if it’s a really complex one like this, then you have to be really close to the people that you trust with it,” says Babbucci. “This is why I prefer to use AWS. I never had any doubt about using AWS.”
Leading Cloud Innovators in Europe
Learn how leading organizations in Europe across industries trust AWS to drive innovation at every level of their business.
Organizations of all sizes across all industries are transforming their businesses and delivering on their missions every day using AWS. Contact our experts and start your own AWS journey today.