The growing reliance on technology poses challenges for visually impaired individuals, especially in receiving accurate and detailed descriptions of their surroundings. Existing models like BLIP and CLIP often fall short in providing rich context. To address this, we introduce Visionary, a mobile app that enhances image descriptions by combining BLIP’s precise image recognition with LLaMA 3’s language processing to add depth and clarity. With a voice-navigated interface and full-screen camera view, Visionary improves the accuracy and contextual relevance of descriptions, promoting greater independence for visually impaired users. Initial evaluations show notable improvements in situational awareness. Beyond simple object detection, Visionary emphasizes capturing the subtle details that make a scene understandable–such as spatial relationships, emotional cues, and fine-grained contextual elements that are often overlooked by existing tools. This ensures that users not only know what is present in their environment but also how different elements interact with one another. By transforming raw recognition into meaningful narratives, the app bridges the gap between vision and comprehension. Its design focuses on accessibility, ensuring that visually impaired users can interact seamlessly without additional complexity. Ultimately, Visionary represents a step toward inclusive technology that empowers individuals to navigate daily life with greater confidence, autonomy, and awareness.