Challenge Area:
Access to legal aid in underserved communities.

Problem Statement:
Low-income individuals lack access to legal resources, leading to unresolved disputes.

Solution Concept:
Create an AI-powered legal chatbot that uses NLP to provide basic legal advice and connect users to pro bono services.

Expected Impact:
Assist 20,000 individuals with legal queries annually.

Next Steps:
Train NLP models on legal texts, ensure compliance with regulations, and pilot with legal aid organizations.

Challenge Area:
Corruption Detection

Problem Statement:
Public procurement processes are prone to corruption, undermining trust in institutions.

Solution Concept:
Create an AI system to detect anomalies in procurement data using graph neural networks to identify suspicious patterns. The PoC ensures data preprocessing for incomplete records and modular code for audit integration.

Expected Impact:
Reduces corruption cases by 30%, saving $500 million in public funds.

Next Steps:
Support global datasets, integrate with transparency platforms, and enhance explainability.