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AI Solution Factory: When Failure Is Not an Option

Reduce failure rates and introduce intelligent automation to business processes with AI Solution Factory from T-Systems

Improve quality and decision making with turnkey AI 

Our experts René Phan and Jörg Heizmann discuss how companies can successfully execute AI projects using our AI Solution Factory.

Your business knowledge, our solution

Does your AI solution provide scalability and reliability? Are you struggling to integrate AI on Edge or within hyperscaler environments?

Make the transition from AI prototype to productive end systems easier and more cost-efficient. 

The AI Solution Factory combines an Application Suite which links to your business logic and systems, together with a Deep Learning factory, which provides a standardized environment for the development of AI services, with a cloud-agnostic approach.

This end-to-end solution eliminates the three main failure rates to ensure AI integrates with your customer systems.

Ready for AI?

Your business deserves success! Make AI simple and efficient with a framework that takes your projects beyond POC to enable model training and automate scale-up into live environments. Get in touch with our AI experts today!

Make your data secure and effective

yellow robot arms build a car body

Almost nine zettabytes of data will be stored by 2024 (IDC). AI enables the creation of new, data-driven business models, but you will want to make sure your information and connections remain secure at all times. The AI Factory is secure by design, and vendor agnostic. It integrates with any hyperscaler platform or Edge Computing strategy to automate the scale-up of AI into your live productive systems. With T-Systems managing the entire AI journey from end-to-end, you can quickly realize the benefits of AI and accelerate your digital transformation. AI doesn’t have to be complicated. With our help, it isn’t!

Whitepaper: Quality Assurance in AI System Development

How do you create high-quality AI systems? Adherence to quality assurance is critical. Read more about the principles, methods and necessary measures that can be used to ensure and enhance the quality of productive AI systems.

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