This paper describes SIIP (Speaker Identification Integrated Project) a high performance innovative and sustainable Speaker Identification (SID) solution, running over large voice samples database. The proposed solution is based on development, integration and fusion of a series of individual speech analytic algorithms which includes speaker recognition, gender/age/language/accent identification, large vocabulary multilingual automatic speech-to-text transcription, expanded by keyword and taxonomy spotting. A full integrated system is proposed ensuring multisource data management, advanced voice analysis, information sharing and efficient and consistent man-machine interactions. The implemented system presented in this paper has been introduced to the international community of law-enforcement agencies animated by Interpol. Preliminary feedbacks collected from end-users indicate their satisfaction with the proposed architecture and its functionality. They also expressed different exploitation needs that we will try to take into account in a further work.