Relief Radar

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Responsible AI

What Inspired Us

We were inspired by the challenge of navigating relief systems during periods of food insecurity. People often miss opportunities simply because information is difficult to access or understand.

What It Does

Relief Radar is an AI-powered OSINT benefits navigator that helps food-insecure individuals, families and community case managers in drought and conflict-affected regions of East Africa, including Somalia, Ethiopia, Kenya and South Sudan, discover food relief programs they may qualify. It continuously monitors public announcements from organizations like the World Food Programme, UNICEF and the Red Cross, along with social media posts and local updates related to food relief. The platform extracts program details, detects duplicate listings, ranks urgent relief signals and converts fragmented eligibility criteria into a simple, searchable experience that helps households find a clear next step.

How We Built It

We developed a real-time ingestion pipeline that aggregates announcements from multiple sources, extracts key information using AI, geocodes program locations and displays active relief options on a live 3D globe. We also created a conversational benefits navigator that asks structured questions about a user's situation and matches them with programs they might be eligible for.

Challenges Faced

Our biggest challenges included handling inconsistent program descriptions, preventing duplicate records, interpreting varying eligibility rules and ensuring recommendations remained informative rather than appearing as guaranteed eligibility decisions.

Accomplishments

Building a fully functional AI-powered benefits navigator that transforms unstructured humanitarian information into actionable recommendations while maintaining transparency and user trust.

What We Learned

We learned how AI can transform unstructured humanitarian information into actionable recommendations while maintaining transparency and user trust.

What's Next For Relief Radar

Expanding our data sources, including SMS and WhatsApp access, improving eligibility matching accuracy, and deploying the platform for pilot testing with partner organizations.