IBM and Bayer 04 Leverkusen Deploy AI-Powered Game Analysis Platform

Dec 5, 2025
IBM and Bayer 04 Leverkusen have developed an AI-based system to enhance football game and training analysis, using IBM Cloud and watsonx technologies to automate data and video processing.

IBM and Bayer 04 Leverkusen have introduced a new AI-powered platform for football analysis, announced in a press release. The system combines data and video analytics to reduce manual work for analysts, scouts, and decision-makers in professional football.

The platform runs entirely on IBM Cloud and integrates multiple IBM technologies, including watsonx.ai Studio for creating and adapting AI models, and watsonx.ai Runtime for embedding AI processes into existing workflows. It uses IBM Cloud Object Storage for video data and IBM Cloud Serverless Computing to handle compute-intensive tasks.

This cloud-based solution automates image recognition and pattern detection, enabling faster and more precise analysis of game and training data. The collaboration aims to optimize data processing, improve scalability, and enhance the user experience for football professionals.

We hope you enjoyed this article

Consider subscribing to one of our newsletters like Enterprise AI Brief or Daily AI Brief.

Also, consider following us on social media:

Stefan Hof AI in Sports Enterprise AI AI Brief AI Brief (X)
Free newsletter

Enterprise AI Brief

Weekly report on AI business applications, enterprise software releases, automation tools, and industry implementations.

Guide
AI voice generators and text to speech services

AI voice generators and text to speech services

Current speech synthesis products for content creators and developers

Whitepaper

Tensordyne Napier: What If One Rack Could Do the Work of Nine?

Tensordyne

This Tensordyne whitepaper presents Napier, an inference-focused AI processor and rack-scale system based on the company’s TDN Math logarithmic number system. It examines infrastructure requirements for large mixture-of-experts and agentic models, compares major inference architecture approaches, and details the TDN AIP processor, TDN72 pod, TDN Link fabric, and Napier Ultra configuration. The paper reports simulation-based performance, cost, and accuracy-validation results, including Tensordyne’s projected comparison of one Napier rack with a nine-rack Nvidia Rubin plus Groq deployment; the chip is reported as taped out and in fabrication.

Read more

You may also like

Free, six days a week

Daily AI Brief: the AI news that matters, in your inbox.