The surge of OSINT data coupled with the exponential increase in computational capabilities, necessitates the integration of advanced algorithms to effectively manage and analyse this information. Traditional methods of data handling are increasingly inadequate due to the sheer volume of data, limited manpower, and the time-sensitive nature of intelligence needs. Recent conflicts testify the same. Employment of advanced AI algorithms such as Natural Language Processing (NLP), Large Language Models (LLM), Web Scraping, Computer Vision, clustering tools and other data mining techniques is now essential. These methods can automate the extraction, analysis and interpretation of data. Identification and weeding out artificially generated content/ deep fake content often called as “Misinformation” also needs to be addressed to produce actionable and accurate intelligence. These activities are not only labour-intensive but also prone to inconsistencies and errors due to human limitation. Therefore, there is a critical need for an OSINT Analysis and monitoring system that can automate these processes to a very large extent that provides relevant, reliable and timely information from vast amount of global data. Post extraction and analysis of OSINT data through user defined contextual filters, intuitive presentation of actionable intelligence is vital which is also proposed to be addressed through an interactive application as the foundation. Broad plan is to develop a 5 module application. 1. Module 1- Source credibility check definition of credibility based on user defined factors/ criterion. 2. Module 2- Open-Source content analysis. 3. Module 3- Social media content analysis. 4. Module 4- Images & video analysis. 5. Module 5- Report extraction and GIS based outputs (Intuitive visualisation) based on open source LLMs). 6. Data mining and aggregation for sifting through vast amounts of data to extract and aggregates the most relevant information. User defined real time monitoring of specific aspects.