Christian Bonzelet
AWS Solutions Architect, DFL Digital Sports
Köln, Germany
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Hi my name is Christian. I am working as an AWS Solution Architect at DFL Digital Sports GmbH. Based in cologne with my beloved wife and two kids. I am interested in all things around ☁️ (cloud), 👨💻 (tech) and 🧠 (AI/ML).
With 10+ years of experience in several roles, I have a lot to talk about and love to share my experiences. I worked as a software developer in several companies in the media and entertainment business, as well as a solution engineer in a consulting company.
I love those challenges to provide high scalable systems for millions of users. And I love to collaborate with lots of people to design systems in front of a whiteboard.
I use AWS since 2013 where we built a voting system for a big live TV show in germany. Since then I became a big fan on cloud, AWS and domain driven design.
Area of Expertise
Topics
Perfecting the Play: Elevating Transcription Accuracy in Sports with Natural-Language-Processing
In the world of sports, the clarity of game narratives is paramount. Traditional transcription services, however, often fumble with the specialized lexicon of sports commentary, especially when it comes to accurately capturing the names of players and technical terms unique to the game. This session unveils Bundesliga’s approach to tackle this challenge head-on, using Amazon Transcribe enhanced with a custom-built NLP and fuzzy-string matching autocorrection feature, powered by Amazon Comprehend.
In this session, the audience will learn:
- how to orchestrate an advanced workflow that not only improves transcription accuracy but also ensures relevance and quality in data handling.
- how leveraging high-quality sports data to create and refine custom vocabularies can significantly reduce word error rates, transforming generic models into specialized transcription powerhouses.
- how to measure the transcription effectiveness, the strategic use of fuzzy-string matching for error correction, and the optimization of custom vocabularies to capture the essence of the game accurately.
This session is designed for advanced practitioners who, while familiar with AWS Transcribe and Comprehend, seek to deepen their understanding and application of these tools. Join us to gain insights into how data curation and innovative NLP applications can turn transcription challenges into victories, ensuring that every call of the game is as clear and accurate as the action on the field.
How Bundesliga creates emotions with personalization
Most companies want to add AI/ML capabilities to their applications and processes but they don’t always have the resources to develop their own ML models. AWS offers the broadest and most complete set of AI services that can easily add intelligence to your workloads. This session will present an overview of these pre-trained ML models and how they enable common business use cases.
I will showcase how we at DFL use Amazon Personalize to build recommendation engines for several Bundesliga products and how the integration of Amazon Pinpoint helps them to engage with their fans while laying down a foundation for future engagement and personalization use-cases.
How to send goal notifications in real-time to hundredthousands of fans on a Matchday?
No one wants to get notified about a goal minutes after it happened on the pitch. By using the official Bundesliga App, the DFL wants their fans to cheer first.
In this session you will gain exciting insights behind the scenes of a Bundesliga match. In particular, how DFL manages to process match events in real time and thus creates value for all Bundesliga fans worldwide with serverless technology.
Let’s build a recommendation engine in 30 minutes.
This is the story of a fictitious company called “Bingewatch”. Bingewatch provides the most complete library of movies on demand for their customers.
Due to the increasingly number of competitors in the market of VoD offerings, Bingewatch faces challenges in maintaining customer engagement and preventing customer churn. A recommendation engine should help them to provide a better personalized experience of movies to watch based on their individual interests.
In session the audience will learn the essential steps of how to build a recommendation engine using Amazon Personalize. Along a real-live scenario, the audience will learn about the key concepts of Amazon Personalize like Dataset-Groups, Datasets, recommender recipes, event-tracker and campaigns. After this session, the audience will know how to use Amazon Personalize for building their very own recommendation engines.
6 Things I wished I knew before building my first GenAI App
Join me for an enlightening talk that dives into Bundesliga’s real-world journey in developing their first Generative AI application to transform web articles into Instagram-like stories. This session explains the LLM’s true role as a pivotal, yet singular component in a broader system landscape for content and media production to engage football fans with new content formats.
You will learn, how we at the Bundesliga
- selected the right LLM for our unique use case,
- changed the game by increasing data quality and diversity,
- approached prompt engineering and evaluated the results of the LLM,
- integrated LLM capabilities into their existing CMS.
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