The event includes a kickoff session by Google, Fi Money and followed by workshops and mentorship by industry experts and and concluding with a 30 hours in person Agentic AI challenge in Bengaluru. This is not just a hackathon—it's a movement that will ignite the imagination of India’s top tech minds. As developers build, pitch, and deploy powerful AI-driven prototypes, the event will redefine what's possible when innovation, scale, and cutting-edge technology converge.Witness and create cutting-edge intelligent agents that learn and act autonomously, leveraging Google's powerful AI stack (Gemini, Vertex AI, etc.).

Join the on-ground hackathon and get exclusive certificates and recognition for your contribution, Learn directly from and get mentored by leading AI experts and industry professionals.

You can stand a chance to take home rewards from an exciting prize pool of INR 39 lakhs :)

Here are problem statements:

1. Managing city data overload - A bustling metropolis like Bengaluru generates millions of scattered data points every minute — from traffic updates and civic issues to spontaneous cultural events. This information is noisy, siloed across different platforms, and becomes outdated almost instantly. The challenge is not just to report news, but to find the signal in the noise and create a living pulse of the city.

2. Empowering teachers in multi-grade classrooms - In countless under-resourced schools across India, a single teacher often manages multiple grades in one classroom. These educators are stretched thin, lacking the time and tools to create localized teaching aids, address diverse learning levels, and personalize education for every child. The challenge is to build a true AI companion that lessens this burden and amplifies their impact.

3.Improving safety at large public events - Large-scale public events like music festivals or rallies are incredibly complex to manage. The fluid dynamics of large crowds create significant risks, from dangerous bottlenecks and crushing to difficulties in locating individuals in medical distress. Security teams need a way to move from reactive monitoring to proactive, intelligent intervention.

4. Providing farmers with expert help on demand - Rohan, a young farmer in rural Karnataka, inspects his tomato crop. A strange pattern of yellow spots has appeared on the leaves of several plants. Is it a fungus? A pest? The wrong kind of fertilizer? The local agricultural office is miles away, and by the time he gets an answer, a significant portion of his crop could be lost. He also faces another challenge: when to sell. The price he gets at the local mandi can vary wildly from day to day. A day's delay could mean the difference between profit and loss. He has a smartphone, but the information he needs—expert pest diagnosis, real-time market prices, and guidance on government subsidies—is scattered, complex, and not available in his native Kannada. He doesn't need more data; he needs an ally, an expert in his pocket who understands his land and his language.

5.Receipt management for Google Wallet - The Challenge: Google Wallet is designed to provide fast, secure access to everyday essentials. However, managing physical receipts remains a cumbersome task for users, leading to lost records, difficulty tracking expenses, and an inability to leverage purchase data for personal benefit. There's a clear need for a seamless way to digitize, organize, and utilize receipt information directly within Google Wallet, enabling users to gain valuable insights into their spending habits and optimize their financial management.

6. Let AI speak to your money (Fi Money MCP) - Fi Money has launched the world’s first consumer-facing personal finance MCP Server — an AI-native infrastructure layer that consolidates, normalises, and structures financial data across 18+ sources, allowing users to connect. AI today can answer general financial questions — but not yours. That’s because your financial life is scattered across banks, mutual funds, stocks, and more. Even the most intelligent AI can’t reason meaningfully without structured, secure access to real data. What’s missing is the infrastructure to connect an individual's complete financial footprint to AI in a way that respects privacy, promotes control, and works across platforms.
While MCP (Model Context Protocol) exists in enterprise AI stacks, it has never been meaningfully applied to consumer finance — until now.