Endometriosis, a persistent ailment affecting 10% of women in their reproductive years (equivalent to approximately 200 million globally), presents a challenge in diagnostic precision. The absence of precise diagnostic tools prolongs the diagnosis period, spanning 7-11 years. Consequently, this delay allows the ailment to escalate into a severe, debilitating condition. Its impact manifests through pronounced pain, fatigue, anxiety, depression, and infertility, leading to a considerable reduction in overall quality of life. The existing imaging modalities fall short of detecting a significant proportion of endometriosis lesions. Furthermore, prevailing disease management approaches lack insight into the location, size, and developmental stage of these lesions. Addressing this critical gap, our proposed solution involves an innovative system designed for comprehensive detection, mapping, and staging of endometriosis lesions. Leveraging robotic artificial intelligence (AI)-powered ultrasound imaging in conjunction with proprietary targeted contrast agents, our system offers a sophisticated approach. This cutting-edge methodology encompasses the integration of a robotic scanning system with the standard transducer of an ultrasound device, achieving a seamless fusion of advanced technologies. The acquired data is streamed and subsequently processed into DICOM volumetric data (3D) using our dedicated software. Employing AI algorithms, the software efficiently identifies and characterizes the highlighted lesions, representing a transformative leap forward in not only the diagnosis and management of endometriosis but also in surgical planning.