Eat-Grass: Meal Partner

Inspiration

The inspiration for Eat-Grass came from a universal daily struggle: "I don't know what to eat !!!"1. We identified that choosing meals has become stressful, particularly for individuals with strict budgets .When someone only has RM10-RM20 to spend, their dining options shrink significantly. We realized that with no platform recommending meals based on budget first, people often waste time deciding, overspend, or settle for food they don't enjoy just to survive the day. We wanted to solve this by creating a "Meal Partner" that prioritizes your wallet and reduces decision fatigue.

What it does

Eat-Grass: Meal Partner is an AI meal planner that focuses on sustainable, budget-friendly choices. Budget-First Meal Discovery: Unlike food apps that show everything, we start from your budget, ensuring every suggestion fits your spending limit (e.g. $RM20$ for 2 meals). Real Locations: We recommend meals based on where you are—Sunway Pyramid, Mid Valley, Pavilion—so the options are actually reachable. Integrated Grocery + Meal AI: We combine meal planning, grocery pricing, and location options in a single interface. Fresh & Non-Repetitive: Our system avoids repeating the same meals, giving users variety without decision fatigue

How we built it

We used a modern tech stack to build our MVP: Cursor: Used for Development. Mobbin: Used for UI/UX references to keep the design User Friendly (Simple & Clean). Anthropic: The LLM used to power our Smart Recommendation Engine. APIFY: Used for data scraping to ensure we had "Real Data" from stores.

Challenges we ran into

The main challenge was addressing the core problem: that limited budgets cause options to shrink. We had to ensure our Smart Recommendation Engine (AI/Rules-Based) could intelligently filter options to fit strict financial constraints while still ensuring the food was enjoyable. Implementing Real Data via Apify Scraper was also critical to ensure we weren't just guessing prices, but providing accurate information.

Accomplishments that we're proud of

We are proud to have built an MVP that successfully integrates: A Budget Input UI that prioritizes the user's wallet. A Location Selector for real-world accessibility. A Smart Recommendation Engine that solves the "what to eat" problem.

What we learned

We learned the importance of sustainable meals. We also learned how to integrate distinct technologies—like Anthropic for logic and Apify for data—into a cohesive "Meal Partner".

What's next for Eat-Grass: Meal Partner

We plan to further develop the Integrated Grocery + Meal AI features. Our goal is to continue refining the platform to ensure users never have to say "I don't know what to eat" again.

Built With

• anthropic
• apify
• mobbin