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Governments worldwide actively support entrepreneurs tackling pressing social issues, aiming to boost economic opportunities for all, generate employment, and accelerate tech-driven progress. Unfortunately, some recipients exploit these funds for personal gain, sidelining projects that could otherwise drive fair governance, community welfare, and environmentally conscious industries. Manually tracking thousands of funded startups is inefficient, allowing dishonest actors to slip through the cracks. This study introduces an AI-powered solution to bridge this gap. The system scans public data—such as LinkedIn activity and online footprints—to identify red flags, like founders holding jobs unrelated to their funded ventures. Advanced language analysis and pattern recognition techniques assess how closely a founder’s current work aligns with their original proposal, simplifying oversight while fostering synergy between public programs and modern technology platforms. By promoting fairness, transparency, and accountability, the system supports several United Nations Sustainable Development Goals, including SDG 8: Decent Work and Economic Growth, SDG 9: Industry, Innovation, and Infrastructure, and SDG 16: Justice, and Strong Institutions. It enables governments to channel resources more effectively to innovators committed to creating lasting social value.

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Impact Analysis of Incubates Funded Under Government Scheme

  • 会议论文

  • 发表日期：

    2026年

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  • Radhika V. Kulkarni,
  • Spandan Papade,
  • Yash Paryani,
  • Saniya Patil,
  • Rahul Madhawani,
  • Prakash Sharma

摘要

Governments worldwide actively support entrepreneurs tackling pressing social issues, aiming to boost economic opportunities for all, generate employment, and accelerate tech-driven progress. Unfortunately, some recipients exploit these funds for personal gain, sidelining projects that could otherwise drive fair governance, community welfare, and environmentally conscious industries. Manually tracking thousands of funded startups is inefficient, allowing dishonest actors to slip through the cracks. This study introduces an AI-powered solution to bridge this gap. The system scans public data—such as LinkedIn activity and online footprints—to identify red flags, like founders holding jobs unrelated to their funded ventures. Advanced language analysis and pattern recognition techniques assess how closely a founder’s current work aligns with their original proposal, simplifying oversight while fostering synergy between public programs and modern technology platforms. By promoting fairness, transparency, and accountability, the system supports several United Nations Sustainable Development Goals, including SDG 8: Decent Work and Economic Growth, SDG 9: Industry, Innovation, and Infrastructure, and SDG 16: Justice, and Strong Institutions. It enables governments to channel resources more effectively to innovators committed to creating lasting social value.