Hackathon 4.0

1. MarketMind AI – AI for Smarter Marketing

Challenge: Reimagine marketing with intelligence.

Teams need to develop an AI-powered marketing solution that helps businesses understand customers, improve campaigns, personalize communication, or make better marketing decisions.

What to do:

• Identify a real marketing problem.
• Use AI/data to understand customer behaviour.
• Build a solution such as an AI recommendation engine, campaign optimizer, customer segmentation model, chatbot, or personalization tool.
• Show how the solution can improve marketing outcomes.

Example: AI system that predicts which customers are most likely to respond to a campaign and recommends the right offer.

2. PeoplePlus AI – AI for People & Talent

Challenge: Create AI-powered solutions for smarter people management.

Teams should address challenges related to employees, recruitment, talent development, engagement, retention, or workforce productivity using AI.

What to do:

• Identify an HR/people-related problem.
• Design an AI-based solution.
• Use data to generate insights or predictions.
• Demonstrate how it can help organizations make better people decisions.

Example: AI-based employee attrition prediction system that identifies employees at risk of leaving and suggests retention actions.

3. FinTech AI – AI for Smarter Financial Decisions

Challenge: Use AI to make financial decisions smarter, faster, and more effective.

Teams need to develop an AI-driven financial solution addressing areas such as investment, lending, fraud detection, personal finance, credit assessment, or financial risk.

What to do:

• Identify a financial problem.
• Use AI/ML and data to analyse or predict outcomes.
• Develop a working model/prototype.
• Explain how the solution improves financial decision-making.

Example: AI-based credit risk model that helps a financial institution assess the probability of loan default.

4. ️ OpsGenie AI – AI for Intelligent Business Operations

Challenge: Make business operations smarter using AI.

Teams should identify an operational problem and build an AI solution that improves efficiency, forecasting, resource utilization, supply chains, inventory, customer service, or business processes.

What to do:

• Identify an inefficient business process.
• Analyse the available operational data.
• Build an AI/analytics-based solution.
• Demonstrate measurable improvement in cost, time, productivity, or efficiency.

Example: AI demand forecasting system that predicts product demand and helps reduce excess inventory and stock-outs.

5. StartupSpark AI – Build, Scale & Disrupt with AI

Challenge: Create an innovative AI-powered startup idea with strong business potential.

Teams have the freedom to identify a real-world problem and develop an AI-based product/service that can become a scalable business.

What to do:

• Identify a significant market problem.
• Develop an AI-powered product/service.
• Define your target customers and value proposition.
• Create a prototype/MVP.
• Explain the revenue model, scalability, and competitive advantage.

Example: An AI platform that helps small retailers predict demand, optimize pricing, and automatically generate personalized promotions.