Users of front office applications such as call center or customer support applications make millions and millions of decisions each day without analytical support. For example, if a support employee gets a new support ticket and needs to decide how much time should be used for problem resolution and which measures should be taken, this is done without analytical insight. As a result, companies cannot optimize their front office departments because analytical insight derived in Business Intelligence (BI) Systems is not available to users of these applications. Our demo shows how to improve a Customer Relationship Management (CRM) System [Lin01] by embedding analytics in an “in context” and “on demand” fashion without requiring any BI System skills. “In context” means that only analytics relevant for decision making on the current UI screen is made available. “On demand” means that the user has the information accessible in “mouse-over” events, i.e. the user decides when to consume which portion of the analytical information. This avoids being flooded with information not needed. The underlying implementation uses UIMA [GS04] to determine the context. Real-time lookup services for the delivery of the analytic insight are dynamically bound to the application UI. In the demo we will show the system at work and explain the architecture, the underlying technologies, and the algorithms used for the embedded analytics. The system has been built in the context of a bachelor thesis.