A Case-based Reasoning (CBR) system uses lazy "generalization" from past similar cases to the present task. Past similar cases are retrieved through similarity estimates between the current problem and the precedent cases that the system has access to. The crucial assumption in a CBR system is that the more similar the current problem is to a precedent , the more similar the solution of is to the solution of . In recent times, CBR techniques have enjoyed an immense popularity among researchers and practitioners of AI, building intelligent tools for a number of applications[Aamodt &Plaza1994]. Techniques for distributed case-based reasoning are being developed with the aim of leveraging the insights gained from building and using such applications but at the same time coping with the distributed nature of the knowledge available in many applications. Viewing Corporate Memories as Distributed Case Libraries (or Distributed Case Bases) provides us with ways to exploit these techniques to develop semantically rich and flexible tools for knowledge management in distributed environments.