Casebase

With Casebase, you systematically build your portfolio of use cases, document the development process in a structured way, establish governance and manage your data & AI roadmap along the entire lifecycle. In doing so, Casebase is the framing software platform that supports use case ideas on their way to innovative, trustworthy data analytics & AI solutions.


Casebase - Solution for comprehensive AI portfolio management including ensuring robust AI governance and AI Act compliance.

As the EU AI Act shapes the legal framework to foster trust, the challenge now shifts to how organizations can effectively implement and manage these changes. The AI use case is moving to the center of the risk assessment and case management will be the key to getting AI Act compliant. Therefor sustainable portfolio management is the basis for getting AI Act-ready and building AI governance structures. 


Understanding the enormity of this task and its significance in the future of an AI lifecycle, we’re here to guide you through this journey with Casebase. 

• Use Case inventory library
  Build and maintain a portfolio of AI and ML use cases
   
• Governance along your AI & ML life cycle
  Definition of quality gates and requirements for design and operations based on compliance obligations and trustworthy AI principles.
   
• Management of responsibilities 
  Clarify responsibilities and make them transparent.
   
• Comprehensive risk management
  Identify and mitigate risk potentials systematically and always keep the overview.
   
• Auditable reporting and traceability
  Make sure that information about your AI initiatives is quick and easy to find as well as understandable for stakeholders.
  
  
  
  
  Background - An  AI Use Case Portfolio Framework
  A comprehensive AI strategy consists of three central pillars: a clearly defined vision, a well-structured portfolio of AI use cases, and an optimal combination of input factors or key resources. Use cases are at the heart of all this. 
   
•  They are the translator of the vision, strategic goals, and operational challenges into specific projects and represent the areas where the company can most benefit from data and AI; whether for a specific product, a service, or a process improvement.
• At the same time, use cases are the connecting element to the needed input factors such as personnel, organizational structures, and technology, to ensure that they can fully unfold their potential in the implementation.

Problem: the porfolio of data & AI applications and the associated processes have grown very heterogeneously in organizations. This means a lack of transparency and systematics in the definition, documentation and prioritization of the AI inventory. There is also a lack of quality standards along the life cycle and insufficient knowledge transfer within a company.