The proliferation of intelligent applications across diverse domains—ranging from smart cities to autonomous vehicles—has accelerated the demand for scalable, low latency, and energy-efficient computing frameworks. Nebula Core presents a novel, scalable multimodal framework designed to seamlessly integrate distributed intelligence across edge and cloud environments. Leveraging adaptive resource orchestration, real-time data fusion, and intelligent workload partitioning, Nebula Core enables efficient handling of heterogeneous data streams including vision, audio, and sensor inputs. The architecture employs a hybrid AI model deployment strategy, balancing edge responsiveness with cloud computational depth to optimize performance, privacy, and scalability. Extensive simulations and real-world deployments demonstrate Nebula Core’s capabilities in reducing inference latency, improving fault tolerance, and scaling across thousands of distributed nodes. This framework sets a new benchmark for future-ready, multimodal edge-cloud systems, fostering advancements in collaborative intelligence and context-aware computing.