The eastern parts of India, Bangladesh, and the North Eastern Region (NER) of India are among the world's most active areas for thunderstorms and lightning, resulting in substantial human and livestock casualties annually. Lightning strikes cause over 500 fatalities in India and approximately 300 in Bangladesh each year, alongside significant property damage and loss of wildlife, such as the death of 18 elephants in Assam in 2021. To mitigate the devastating effects, this study developed a pilot-scale forecasting system for lightning and thunderstorms over the NER of India, leveraging space-based platforms, ground-based detectors, and numerical models. Data sources included the WWLLN (World Wide Lightning Location Network), India's national lightning detection network, Doppler Weather Radar (DWR), and satellite data from INSAT 3D/3DS. The WRF-ELEC model was employed for forecasting, assimilating lightning data via nudging techniques, and achieving forecasts with up to 75% accuracy for lead times of up to four hours. A GIS-based system was used to track convective systems and predict impacted areas at a village level with a one-hour lead time. This system integrates lightning detection, satellite imagery, and DWR data, enabling the identification of affected populations and land use, thereby aiding in disaster preparedness and mitigation. The study demonstrates the potential of integrating earth observation data, in-situ measurements, and numerical models to provide location-specific and time-sensitive lightning forecasts. Coupled with awareness campaigns on safety measures during lightning, this approach offers a robust mechanism to reduce casualties and property damage. Scaling this system beyond the pilot region could significantly enhance disaster risk reduction in other lightning-prone regions.