AI for Good Hackathon: How APJ innovators showcased real-world impact with Snowflake and AI

Across APJ, developers, data engineers and artificial intelligence practitioners challenged themselves to solve real-world challenges for the AI for Good Hackathon. Designed to push participants beyond dashboards and into building scalable, actionable applications, the program offered innovators a platform to create solutions that blended AI, automation and data engineering.

The hackathon invited data engineers, scientists, analytics professionals, AI/ML experts, SQL developers and application builders to create measurable social impact through the strength and intelligence of their applications. Participants used technologies including Python, Java, Scala, AI/ML frameworks, Snowflake Worksheets, Data Clean Rooms, Horizon, Cortex AI, Streamlit, Snowpark, and Dynamic Tables.

Over the course of nearly three months, competitors from each region - India, ASEAN, ANZ, Korea, and Japan - put their ideas to test, from submission, to prototype development and pitching to showcase a solution that could create real-world impact. The final showcase took place in January 2026.

“A hackathon built around AI for good is not just a competition, I would say it's an invitation to think differently about what technology can do and who it can do it for”, said First Prize Winner (India), Krishnan Srinivasan.

Participants could choose from five problem statements centered on social impact. Challenges ranged from building privacy-safe collaboration between banks and insurers, to building reusable Native Apps for repetitive public-sector workflows, improving stock visibility for hospitals and NGOs, creating AI-assisted housing inspection tools, and designing broader AI-for-Good applications in sectors such as health, education, safety, and climate. A common thread stretched across all categories: can the brightest innovators today use Snowflake’s AI and data stack to build socially impactful applications that are scalable, secure and accessible?

The competition offered regional travel and stay vouchers, with first-prize winners receiving rewards worth ₹18,000 ($200), second prize winners receiving ₹14,000 ($150), and third prize winners receiving ₹10,000 ($100). Runner-up prizes were also awarded across regions. Beyond rewards, many participants shared that the hackathon gave them an opportunity to experiment, validate ideas and apply AI to problems that matter.

Big ideas, bigger wins

Krishnan Srinivasan from Cittabase Solutions, built the Hackathon-winning “ADA Insights,” an education-focused dashboard designed to provide personalized and actionable intelligence around student dropout risks and academic guidance. Reflecting on the experience, he noted that while AI is often associated with engagement and revenue generation, its real potential lies in solving societal challenges. His solution leveraged Snowflake Cortex AI features including Cortex Analyst, Cortex Search, and Snowflake Intelligence to turn siloed school data into timely interventions.

Second prize winner Swasti Singhal from Bot Consulting focused on AI-assisted home and building inspections. Inspired by the challenges families face during subjective home inspections, her team used Snowflake’s Cortex AI capabilities to detect structural defects and generate natural-language summaries from inspection findings. She emphasized that the experience reinforced the importance of solving practical problems over building flashy AI features, while also highlighting how crucial clean, usable data is to any successful AI workflow. “Winning second prize was honestly a very proud moment for us, but I think what meant even more was the validation that the problem we chose and the way we approached it. It actually resonated with people. It felt like we built something that genuinely can make a difference”, she said.

Third prize winner Sai Teja T from Wells Fargo tackled inventory management inefficiencies by building an application that transformed complex warehouse data into simple, conversational insights. Using a multi-agent architecture powered by Snowflake and Streamlit, the system enabled users to ask natural-language questions about stock levels, consumption trends, and purchase forecasts. Reflecting on the hackathon, Sai addressed innovators directly, saying “keep exploring and pushing boundaries - even if you don’t get selected in a hackathon. Or just try, because maybe you may get it. The things that you learn in a hackathon is something that you wouldn’t be able to learn in 6 months or more. The learning curve is pretty huge when you participate in a hackathon because of the deadline pressure. It's something new, and many people are working on it at the same time. So put that energy in.”

AI for APJ: local problems, global innovation

The hackathon also highlighted its increasingly global footprint, with winners and runner-up participants representing India, the Philippines, Thailand, Indonesia, and Australia. Regional winners included Mikaela Molina (Philippines, 1st Prize), Mark Samuel Nicasio (Philippines, 2nd Prize), and Thanaruk Kocharat (Thailand, 3rd Prize). ANZ consolation prizes went to Abdulkareem Okadigbo, Doran Huh, and Jarrad Waye from Australia. India consolation winners included Kinshuk Gaurav Singh, Kritika Benjwal, Nga Nguyen, Pratush Maheshwari, and Ritesh Meena. ASEAN consolation winners included David Hendrya, AISYAH CURRENTS, Assifa Khairu Nisa, Dama Dhananjaya Daliman, and Fudholah Fukhoiroh from Indonesia, underscoring how AI for Good continues to inspire builders across borders.