A growing number of applications requires the ability to analyze massive amounts of streaming data in real-time. Examples of such applications are: market data feed processing of the output of large scale ad-hoc networks, etc. The project aims at providing a highly scalable cloud computing platform to enable a new breed of services. The core is the data streaming platform, StreamCloud, that will be able to parallelize the processing of information flows in large clusters of 100s sites. Current approaches fail to scale for massive information flows. Stream aims at boosting the scalability of current approaches in 1 to 2 orders of magnitude. Stream platform will provide elastic computing, so the computing resources as used as required by the incoming load. Below the core, there is a high performance communication layer that enables an efficient interaction among sites with access between node memories of tens of microseconds in contrast with tens of milliseconds using current technology. Additionally, this layer will provide parallel IO and low cost storage for huge amounts of information. Above the core, there is a data mining layer offering higher level services to ease the development of applications processing the information flows. On top of the data streaming platform there is the application layer in which user applications & services will run.