Neocambrian AI launches India-focused robotics data factory for Physical AI models

Home services and robotics-focused data collection startups are increasingly drawing attention amid the ongoing debate around Physical AI-linked human activity datasets. Now, another startup has formally entered the space. Founded by entrepreneur Abhinav Kukreja, Neocambrian AI has announced its launch with a focus on building large-scale human action datasets for robotics and embodied AI systems. Kukreja had earlier founded DataVantage, an AI powered marketing workflows for medium and large technology enterprises. The announcement comes days after Entrackr reported on Pronto ’s experiments around Physical AI-linked data collection. Another startup, Snabbit , also confirmed to Entrackr that it had earlier been approached by US-based startup Human Archive for similar initiatives but eventually decided not to proceed. In a detailed public note, Kukreja described Physical AI as the next frontier of artificial intelligence, arguing that robotics lacks “internet-scale datasets” comparable to the text datasets that enabled large language models. According to the company, Neocambrian AI is building what it calls a high fidelity, pre-training scale database of human action, using egocentric video capture systems, motion tracking hardware, stereo capture rigs, and upgraded UMI devices for robotics training. The startup claims to have set up India’s first and only robotics data factory and plans to provide thousands of hours of collected data free of cost to Indian researchers working on vision-language-action (VLA) and world models. Kukreja also framed India as a potential global hub for Physical AI datasets, citing the country’s large workforce, diverse real-world environments, and operational experience in distributed services. The emergence of such startups highlights the growing interest in collecting structured human behavioural data for training next-generation robotics systems, even as concerns around privacy, worker consent, and ethical data collection continue to intensify.