EcoScout

Inspiration

Have you ever wished every product you buy came with a sustainability label? Consumers want to make eco-friendly choices, but the true environmental costs—CO₂ emissions, water usage, recyclability, and ethical sourcing—are often hidden. We wanted to create a tool that makes sustainability transparent and actionable, helping shoppers reduce their impact with confidence.

What it does

EcoScout is your AI-powered eco-shopping assistant.

• Scan a product barcode or type in its name.
  
• Get an EcoScore (0–100) that measures environmental impact.
  
• View a breakdown across CO₂ footprint, recyclability, water use, and ethical sourcing.
  
• See greener alternatives suggested instantly.
  
• Get personalized insights based on your shopping habits.
  
• Track your overall impact with a dashboard that shows how much CO₂, water, and waste you’ve saved.
  

How we built it

We built EcoScout using Base44 for both frontend and backend orchestration:

• Frontend: Base44 drag-and-drop UI for scan forms, product cards, and recommendation lists (mobile-friendly PWA).
  
• Backend AI Agents:
  
  • Eco-Score Agent – applies a weighted sustainability formula:
    

EcoScore = ((w_CO2*score_CO2) + (w_Recycle*score_Recycle) + (w_Water*score_Water) + (w_Ethics*score_Ethics)) / (w_CO2 + w_Recycle + w_Water + w_Ethics)

• Recommendation Agent – finds greener alternatives.
  
• Personalization Agent – adjusts results to user values (vegan, plastic-free, etc.).
  
• Impact Tracker Agent – records user impact over time.
  

Challenges we ran into

• Inconsistent product IDs: The same product produced different scores when AI generated slightly different names. We solved this by designing a deterministic product ID system (barcode when possible, otherwise normalized attribute hashes).
  
• Data gaps: Not all products have full LCA data. We had to design fallback rules and approximations while staying transparent.
  
• Balancing complexity: Real Eco-Score and LCA frameworks are detailed; translating them into a hackathon-friendly but credible formula was a challenge.
  
• Time pressure: Deciding which advanced features (like Fetch.ai marketplace integration) to build vs. leave for the future.
  

Accomplishments that we're proud of

• Building a fully working pipeline of AI agents within the Base44 ecosystem.
  
• Creating a transparent, explainable EcoScore formula that mirrors real-world LCA and Eco-Score frameworks.
  
• Designing an interface that makes sustainability easy and engaging for everyday users.
  
• Solving the duplicate product score problem with a deterministic ID and caching solution.
  

What we learned

• How to design multi-agent workflows that collaborate instead of one monolithic AI.
  
• The importance of user experience: eco-feedback must be simple, clear, and visual.
  
• That sustainability data is fragmented—but structuring it into a unified score helps people act.
  
• How real-world frameworks like Life Cycle Assessment (LCA) and Eco-Score can be adapted into accessible, hackathon-ready tools.
  

What's next for EcoScout

• Expand Data Sources: Integrate with Fetch.ai decentralized marketplaces for verified sustainability data.
  
• Retail Integrations: Offer EcoScout as a plugin for online stores (Shopify, Amazon, grocery apps).
  
• Gamification: Add leaderboards, challenges, and social sharing to keep users motivated.
  
• Global Expansion: Localize EcoScout for different regions with tailored sustainability data.
  
• Long-term vision: Make eco-friendly shopping the default experience—helping millions reduce their environmental footprint with every purchase.

Built With

• ai
• aiagents
• api
• base44
• base44aiagents
• base44cloud
• cloud
• co?-footprint
• eco-score-agent
• ethical-sourcing)-**cloud-/-hosting**-?-base44-integrated-cloud-environment-**programming**-?-javascript/typescript-(for-custom-logic)
• googleauth
• impact-tracker-agent-**progressive-web-app-(pwa)**-?-mobile-friendly-deployment-**apis-/-data-sources**-?-product-information-apis
• javascript
• packaging-recyclability
• personalization-agent
• react
• recommendation-agent
• sustainability-datasets-(e.g.
• water-usage