Discover App Moderization with AI Assessment

Sopra Steria Norway

Modernize and Migrate Apps to the Cloud twice as fast with AI

Target audience are CIO, CTO, CDO, CFO, COO, IT Managers and Development Managers.

Context Many organisations are struggling with old IT systems that are expensive to maintain, complex to update and that limit innovation. With a lack of developers with legacy competency and increasing demands on performance, security and scalability, modernisation becomes crucial. AI technology revolutionises the process by automating code analysis, documentation and migration, drastically reducing costs and risk, while making systems more flexible and future oriented.

Our approach • Discover – AI maps and documents current systems, identifies technical debt and suggests future architecture. • Accelerate – A Minimum Viable Product (MVP) is quickly built with the help of AI to demonstrate the value of the modernisation. • Develop – Continuous development of the new solution with AI-driven code generation and testing. • Automated code analysis – AI tools offer deep insight into legacy code and make it easier to understand and document. • Security and quality assurance – AI supervises, tests and secures stability in the modernised application. • Cloud optimisation – Transition into a flexible architecture adapted to modern cloud solutions and micro services.

Output • End report containing o Vision and roadmap for modernized Apps o A recommendation for modernization/migration strategy o Estimate for rearchitected solution o Proof of Value with use of AI • Architecture and Cloud Design o How to utilize Azure PaaS, Azure DevOps, Github Copilot, Azure AI Platform, etc. o How to consume Azure the best to meet your needs

https://store-images.s-microsoft.com/image/apps.20170.b3e88697-6146-44a8-9892-43a6a1a2d353.74fa1843-390e-47f1-a3f5-22a94cf9c572.4d8a790b-bf5c-4487-bcc2-e088993ca934
https://store-images.s-microsoft.com/image/apps.20170.b3e88697-6146-44a8-9892-43a6a1a2d353.74fa1843-390e-47f1-a3f5-22a94cf9c572.4d8a790b-bf5c-4487-bcc2-e088993ca934