Muhammad Yousif@m_yousif

CheapestBuy.AI – AI-Powered Smart Grocery Finder 🚨 Problem Grocery shoppers often waste time manually comparing prices across multiple stores (Carrefour, Metro, Imtiaz, Daraz, etc.). Price fluctuations, hidden delivery costs, and unreliable reviews make it difficult to know if they’re truly getting the best deal. This leads to overspending, decision fatigue, and frustration — especially for budget-conscious households. 💡 Solution CheapestBuy.AI solves this with an AI-powered grocery shopping assistant that: 🔎 Searches & Compares prices, delivery times, and availability across multiple platforms. 🤖 Uses multi-agent workflows to analyze results and recommend the top 3 cheapest & highest-rated options instantly. 💬 Performs sentiment analysis on reviews to filter low-quality products. 🔉 Offers voice search powered by Mistral AI for hands-free shopping. 🖥️ Provides a clean, beginner-friendly Streamlit UI with filters & price history. 🪸 Is securely registered on Coral Protocol MCP, making it embeddable as a widget for supermarkets, e-commerce stores, or delivery apps. 💳 Includes a Solana Pay demo checkout, showcasing future-ready blockchain payment integration. 🌍 Impact CheapestBuy.AI empowers users to save money and time by getting the best prices with just one search. For businesses, it offers a scalable, embeddable solution that improves customer satisfaction and engagement. By combining AI, secure registry, and future-proof payments, CheapestBuy.AI sets the standard for the next generation of smart, automated grocery shopping experiences.

Personalized TutorBot is an AI-powered multi-agent educational assistant designed to make AI and programming learning accessible, engaging, and personalized. Built using Blackbox-powered LLMs, FastAPI, and React, TutorBot intelligently guides learners through a customized journey via a chatbot interface. The system begins by understanding user goals and skill levels through natural conversation. Based on this, it dynamically generates personalized roadmaps, tailored tutorials, hands-on coding exercises, and intelligent code reviews—adapting in real time to learner progress. TutorBot includes key components like secure user authentication, an intuitive chatbot UI, an AI roadmap agent for goal-based planning, a tutorial agent delivering daily lessons, and a coding exercise agent that adjusts challenge levels. An integrated Replit-based IDE allows learners to code and test within the platform. The review agent offers instant, context-aware feedback on submitted code. All progress is tracked through a visual dashboard, helping users monitor their growth. With zero cost, zero setup time, and 100% personalized learning, TutorBot breaks financial and geographic barriers, scaling easily to serve thousands. Future enhancements include voice support for accessibility, gamified learning with XP and leaderboards, and an AI progress coach to offer proactive feedback and learning path adjustments—redefining how AI and coding education is delivered.

Schools in Africa have several needs. We want to focus on the lack of adequate infrastructure and the limited access to modern technologies, which restricts students' ability to participate in online learning programs or access digital educational resources. AI-powered platform. Initially developed on Streamlit for rapid prototyping, this platform integrates multiple technologies to deliver an educational experience rooted in African culture. It leverages OpenAI’s GPT-3.5 for a multilingual chatbot that answers questions using culturally relevant African examples. Stability AI generates localized visual lessons, such as science diagrams featuring native plants, while ElevenLabs provides text-to-speech functionality for audio responses. Additionally, the mentorship system organizes requests in a CSV database and includes an admin dashboard for managing student needs.

Patient Input: Patients can enter their symptoms, medical history, or concerns into the app. This could range from describing a specific condition, reporting a set of symptoms, or even sharing their daily lifestyle and medical background. LLM-Driven Analysis: The app utilizes advanced language models that analyze the input provided by the patient. These models are trained on a vast dataset of medical knowledge, helping to identify potential conditions or concerns based on the data provided. Preliminary Medical Report: Based on the patient’s input, the app generates a preliminary medical report. This report offers insights into possible diagnoses, recommended next steps, and any potential lifestyle adjustments. It serves as an informative starting point for further medical consultation. Improved Doctor-Patient Interaction: The app enables more effective communication between the patient and the healthcare provider by delivering well-organized, structured reports. This helps doctors understand the patient's concerns more quickly, making their consultations more efficient. The report is not a definitive diagnosis but a tool to guide the doctor’s examination.

The limited accessibility of space-related data and insights presents a critical challenge, impeding researchers, educators, and the public from driving innovation, advancing education, and making informed decisions in the domain of space exploration. To address this challenge, we have developed an advanced educational chatbot designed to cater to diverse learning levels, including students, professionals, and children. This intelligent chatbot dynamically adapts to the user's educational background, enabling individuals to ask space-related questions and receive accurate, personalized responses. By simplifying complex space concepts into clear, comprehensible explanations, the chatbot makes space education more accessible. It empowers learners of all ages and backgrounds to explore the intricacies of space science, fostering curiosity and facilitating effortless knowledge acquisition.

🔍Create AI-driven solutions using open-source technologies to optimize public sector network management—planning, procurement, and maintenance—for scalable, sustainable school connectivity in underserved regions. 📅 Join us January 24-26: Participate online or in person in Geneva to develop innovative solutions with peers globally. 👨‍🏫 Work alongside industry mentors for insights and guidance on your projects. 🏆 Compete for a chance to join the Lablab NEXT incubator program! 🧑🏻‍💻 Sign up before the Kick-Off Stream to secure your spot!

🕒 2 days to innovate and build groundbreaking applications using the latest generative AI tools 🌟 Expert mentors will guide you every step of the way. 🤝 Work alone or form a team to build something extraordinary. 🏆 Win an opportunity to participate in the Lablab NEXT acceleration program. 🧑🏻‍💻 Sign up before the Kick-Off Stream to secure your spot!

🔍Create AI-driven, open-source solutions to optimize public sector network management in critical areas like predictive maintenance, total cost optimization (TOC), and energy efficiency—enhancing public sector networks' scalability, efficiency, and sustainability in underserved regions. 📅 Join us February 28–March 2, 2025: Participate online or in person in vibrant Barcelona, on the sidelines of MWC 2025, to collaborate with peers worldwide and shape the future of public sector connectivity. 👨‍🏫 Work alongside experienced industry mentors who will provide guidance and insights to elevate your solutions. 💰 $5,000 prize pool for the winners! 🏆 Compete for a chance to join the lablab NEXT incubator program! 🧑🏻‍💻 Don’t wait! Sign up now to secure your spot before the Kick-Off!