SupplyShield 2.0 is an AI-powered logistics intelligence system designed to monitor global shipments in real time, detect risks proactively, and automate decision-making and communication to reduce costly disruptions. Supply chains today face unpredictable events — weather delays, port strikes, roadblocks, and geopolitical risks — yet most systems rely on manual reporting, slow updates, and siloed communication. These gaps lead to delayed actions, misinformed stakeholders, and massive financial losses. SupplyShield 2.0 solves this with a full-stack AI-driven dashboard that uses real-time inputs (shipment logs, weather, news) to identify potential disruptions. It uses Claude LLM via Anthropic to summarize risks, suggest optimal decisions (like rerouting or expediting), explain severity levels, and even draft professional messages or Slack updates for stakeholders — automatically. The system is built using Streamlit for interactive visualization, LangChain + LangGraph for smart logic flows, and ChromaDB to store historical decisions and learn from them. It integrates OpenWeatherMap, GNews, and Slack Webhooks, providing a 360° view of each shipment — including weather at its current location, breaking news alerts, AI-generated risk summaries, and cost comparisons between action choices (e.g., penalty vs air freight vs rerouting). Users can upload new shipment entries or choose from samples. The app allows for one-click PDF and CSV report exports and features an internal chatbot interface that remembers the current session. It is built with modular architecture, real-time visuals (Plotly maps and charts), memory-driven chat, and customizable alerts. By automating insight, communication, and contingency logic, SupplyShield 2.0 helps companies reduce operational losses, speed up decision-making, and improve reliability in their global supply operations. It combines the power of LLMs with logistics domain intelligence to build the next-generation smart supply chain layer.

A tool for large enterprises that allows distributed teams to collaborate on coding projects with AI-enhanced support. Replit provides the cloud-based environment for real-time collaboration, Cursor optimizes team efficiency with predictive code generation and error detection, and Claude acts as a Tech Lead, helping with code reviews, suggesting optimizations based on the team's previous code, and ensuring the team follows best practices. Multiple developers work together in Replit, with Cursor helping teams refactor, debug, and enhance their code. Claude can provide high-level oversight, such as suggesting improvements based on the overall codebase, offering advice on architecture or optimization, and ensuring security and compliance protocols are followed. This tool would significantly enhance team productivity and code quality, ensuring consistency and efficiency across large development projects. It would be especially valuable for enterprises that rely on remote or distributed teams.

Thematic learning: An application that generates a complete course on the theme that the user has entered: It generates the course, the application exercises as well as the evaluations. It also rates users and gives a rating in 100% of reviews. The project successfully demonstrates the potential of AI in the educational field by automating the creation of course content, assessment questions and responding to student queries as well as their assessment. This not only improves the efficiency of educators but also ensures high-quality learning. Materials for students. The inclusion of full functionality marking functionality by automating the grading process and providing valuable feedback

A medical bot is a conversational AI tool that can provide medical information and support to patients. Medical bots can be used to answer questions about symptoms, treatments, and medications, as well as to provide coaching and support for patients with chronic conditions. The challenge is to develop a medical chatbot application using cutting-edge AI technology that can provide accurate and coherent medical information and assistance in real-time. This project requires addressing issues related to algorithmic precision, diverse medical data integration, medical knowledge incorporation, and real-time response capabilities. Our medical chatbot solution represents a cutting-edge fusion of AI technology and medical expertise. It stands ready to assist users with accurate, real-time medical information and guidance. With diverse data sources, a deep understanding of medical concepts, our chatbot ensures that individuals can access essential healthcare information with ease. Whether it's offering advice on common symptoms or providing recommendations for seeking professional medical help, our chatbot is a reliable and user-friendly healthcare companion

🗓️ This will be a 7-day virtual hackathon from 16-23 December 💻 Build AI application with the latest large language model-powered technology by Cohere 💡 Get the chance to work with the best AI professionals in the industry and learn from them ✔️Entry level = 0. You’ve just started with AI? Are you an experienced Data Scientist? Or maybe you are a Designer or Business Developer? Join us! We need your domain knowledge! 🐱‍💻 Register now and let's get started! It’s free!

🔥 3 days to create your app 🌐 Join the hack in London, Tel Aviv and virtual on lablab.ai 🤝 Build alone, or create your team on lablab.ai 🚀 Have the opportunity to go-to-market and grow your product on the monday app marketplace 📌 Each team member must register individually. Please note that space is limited for our in-person hackathons. Spots will be allocated on a first-come, first-approved basis.

🚀💻 Be the first to build an AI App on Google's models! Hackathon on July 7-10. 🔬🌐 Try new Vertex AI features from Google Cloud Platform. 🤝🌍 Learn from AI leaders and connect with like-minded people. 🛠️📱 Build apps with the world's best AI tools! 💡🌍 Solve real-world problems with Generative AI models