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  Predictive hunger intelligence platform powered by MeDo AI.

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  Warm humanitarian AI landing experience focused on early hunger prevention

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  National intelligence dashboard with real-time district risk monitoring

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  Interactive geospatial hunger-risk heatmap powered by predictive analytics

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  District severity intelligence and intervention prioritization system

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  Predictive analytics engine forecasting nutrition-risk escalation trends

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  AI-generated intervention insights with actionable humanitarian recommendations

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  Automated district reporting and intelligent risk assessment workflows

Inspiration

Millions of children silently attend school while facing hunger and malnutrition. In many regions, intervention only happens after attendance drops, health conditions worsen, or students leave education entirely.

We wanted to explore how AI and predictive analytics could help organizations identify hunger-risk patterns earlier and support smarter nutritional intervention before the problem becomes critical.

That vision led us to build NourishIQ.

What it does

NourishIQ is an AI-powered nutrition intelligence platform built using MeDo AI that predicts child hunger-risk zones using attendance trends, meal participation data, regional indicators, and food-price patterns.

The platform helps:

• schools monitor nutrition-risk trends
• NGOs prioritize food support intelligently
• district authorities identify high-risk regions
• organizations make faster, data-driven interventions

Core capabilities include:

• AI-powered hunger-risk prediction
• district-level hunger heatmaps
• predictive analytics dashboards
• AI-generated intervention insights
• school intelligence monitoring
• nutrition trend analysis
• district drill-down analytics

How we built it

NourishIQ was designed as a production-style social-impact intelligence platform focused on scalability, analytics, and real-world usability.

Frontend:

• Next.js 15
• TypeScript
• TailwindCSS
• Framer Motion
• Recharts
• React-Leaflet

Backend:

• Node.js
• Express.js
• PostgreSQL
• Prisma ORM

AI Layer:

• MeDo AI-powered predictive insight architecture
• AI-generated nutrition-risk summaries
• trend intelligence and anomaly detection
• intervention recommendation workflows

We also created realistic synthetic datasets to simulate:

• district-level hunger risks
• attendance decline patterns
• meal participation fluctuations
• food-price inflation trends
• intervention scenarios

Challenges we ran into

One of the biggest challenges was balancing:

• realistic infrastructure design
• hackathon development speed
• meaningful social impact
• scalable analytics architecture

Building visually intuitive heatmaps and analytics systems while keeping the experience emotionally meaningful and easy to understand was another major challenge.

We also focused heavily on designing a platform that felt like real national-scale infrastructure rather than a typical student dashboard project.

Accomplishments that we're proud of

We are proud of building a platform that combines:

• social impact
• predictive AI
• large-scale analytics
• intuitive visualization
• actionable intervention intelligence

The hunger heatmap, district intelligence dashboard, and AI-generated intervention insights became the strongest parts of the experience.

What we learned

During development we learned:

• how predictive analytics can support social-good systems
• how important visual storytelling is for data intelligence platforms
• how to structure scalable dashboard architectures
• how AI can transform fragmented social data into actionable insights

We also learned that solving social problems requires clarity and usability as much as technical sophistication.

What's next for NourishIQ

Future plans include:

• real-time government dataset integration
• expanded MeDo AI intelligence workflows
• regional language support
• NGO collaboration systems
• live intervention tracking
• field-worker mobile accessibility
• district and state deployment pilots

Our long-term vision is to evolve NourishIQ into scalable nutrition intelligence infrastructure capable of enabling earlier and smarter child hunger intervention across communities.

Built With

• express.js
• framer-motion
• medo-ai
• next.js
• node.js
• postgresql
• prisma-orm
• react-leaflet
• recharts
• tailwindcss
• typescript
• vercel