In the intelligence domain, the collection and processing of information and intelligence from multiple Intelligence, Surveillance and Reconnaissance (ISR) sources (including sensors, human, open sources, etc.) is essential to produce actionable intelligence of high value in order to counter threat. In current practice, the outputs of different sources are more often separated from one another and thus, crosschecking is limited. Further, the traditional intelligence cycle model lacks in representing the process from an all-source perspective. In this paper, we propose an all-source intelligence process model that represents elements of the intelligence process from an all-source perspective. The proposed model is composed of several activities and processes: intelligence tasking; direction; single source collection & processing; all-source discovery & fusion; dissemination; and evaluation & feedback. Three levels of detail of the model are provided. The proposed model presumes a collaborative approach that enables the analysis of a greater quantity of single source data by sharing analysis tasks and results between all actors from different military and non-military intelligence organizations. In addition, this paper discusses the issues and challenges to the effectiveness of all-source intelligence model and presents factors that enable such a collaborative approach.