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Global analyses of tree diversity and function are strongly biased geographically, with poor representation from South Asian forests. Even though data from India - representing two-thirds of South Asia and spanning a wide range of tree-based biomes - exists, a barrier to syntheses is the absence of accessible and standardised data. Further, with increasing human footprint across ecosystems, data from Indian landscapes, with their long history of human-nature interactions is a key link to understand the future of tropical forested landscapes. Combining literature searches with manual data retrieval, we assembled INvenTree, the INdia Tree Inventory dataset, the largest meta-dataset of peer-reviewed publications (n = 465) from 1991-2023 on geolocated plot-based tree inventories of multispecies communities from Indian ecosystems, in aggregate covering 4653.64 ha and all of its vegetated biomes. Using the INvenTree dataset, we show extensive sampling across tropical moist and dry forests, the dominant ecosystem types in the country. We also identify ecological and conservation sampling priority regions based on forest cover and loss and set a blueprint for future sampling efforts in the country. However, most studies are small scale (median = 2 ha) and data across studies is not openly accessible (73.33 % of studies representing 83.43% of the sampled area), potentially hindering inclusion into regional or global syntheses. Significantly, we show majority authorship from within the country; 82.8% of corresponding authors were from India and 73.33% of the studies had all authors affiliated with Indian institutions. Based on extensive Indian …