Discover how IIT Ropar, Syngenta, and Google are fostering agricultural innovation through ‘HACK CORE 2026’, inviting Indian innovators to develop cutting-edge AI solutions for sustainable farming.
Key Points
- IIT Ropar’s ANNAM.AI, Syngenta, and Google launched ‘HACK CORE 2026’, a national AI hackathon for agriculture.
- The hackathon seeks AI-driven solutions for crop health, pest management, soil intelligence, and climate-resilient farming.
- Innovators across India are invited to apply by July 21 to develop sustainable agricultural technologies.
- Winning teams will receive a trip to Syngenta’s Research Centre in Italy and Google Cloud credits.
- Participants gain access to expert mentorship and valuable knowledge exchange with agronomy specialists.
IIT Ropar’s ANNAM.AI, a Centre of Excellence (CoE) for artificial intelligence in agriculture, has launched a national AI hackathon ‘HACK CORE 2026’ in collaboration with Syngenta and Google. It has invited innovators to develop AI-driven solutions for crop health, pest management, soil intelligence, climate-resilient farming and the wider adoption of biological products across India.
HACK CORE 2026: Driving Agri-AI Solutions
Applications for HACK CORE 2026 will close on July 21, IIT Ropar said in a statement. The hackathon is open to students, researchers, developers, startups and innovators from across India.
The winning team will visit Syngenta’s Research Centre in Atessa, Italy, to see first-hand cutting-edge facilities and tools in biologicals research. The winning team will also be awarded Google Cloud credits, giving them access to Google’s cloud platform and a range of infrastructure, data, AI and software to support their work. Participants will gain access to expert mentorship, hands-on ground-level research opportunities, and valuable knowledge exchange with agronomy experts from ANNAM.AI and Syngenta, it added.
Disclaimer: News content is sourced from the stated source. Headlines, summaries, section headers, and images are automatically generated or selected using AI/algorithms and may not always be fully accurate. Readers are advised to refer to the full article for complete context.
