Muhammad Hanzla@muhammad_hanzla_451

ResearchAI is a comprehensive web application designed to streamline the academic research process. It empowers researchers, students, and academics to manage, analyze, and interact with scientific papers more effectively. Users can upload PDF documents, and the system will automatically process and index them. The platform offers several key features: AI-Powered Analysis: Leverages AI models to perform in-depth analysis of research papers, helping to identify key findings, methodologies, and potential research gaps. Interactive Chat (RAG): Includes a sophisticated "ask anything" feature that allows users to have a conversation with their documents. The system uses Retrieval-Augmented Generation (RAG) to provide accurate, context-aware answers based on the content of the uploaded papers. Content Generation: Assists with academic writing by providing tools to draft content, generate outlines, and summarize complex information. Project and User Management: Features a full dashboard for managing projects, tracking analysis history, and handling user authentication. The application is built with a modern tech stack, featuring a Next.js frontend for a responsive user experience and a robust FastAPI backend to handle file processing and AI-powered analysis.

Agentic Foodie is a voice-powered restaurant ordering app built using Streamlit for the frontend UI. It features a modern interface for browsing the menu, recording voice input, and managing orders. Key Streamlit components like st.columns, st.button, and st.session_state handle layout and interaction, while custom CSS enhances styling and responsiveness. audio_recorder_streamlit enables in-browser audio recording, returning WAV bytes. These are processed with pydub (AudioSegment) and speech_recognition (Recognizer with recognize_google) to convert audio to text for voice-based interactions. Groq API (LLaMA 3) provides the core NLP via HTTP requests made using the requests library. The app sends user messages and history to the API and receives structured JSON responses with intents, item IDs, quantities, and replies. Rate-limiting is managed using x-ratelimit-remaining-requests and timestamps with the time module. JSON is used throughout for defining menus, promotions, and exchanging data with the Groq API. The io module (io.BytesIO) handles in-memory audio processing for seamless transcription. A custom Multi-agent Control Plane (MCP) organizes tasks like checking availability and suggesting items. Agents are registered using decorators (e.g., @inventory_agent.task) and simulate modular multi-agent interactions. Overall, this tech stack enables an AI-driven, interactive restaurant ordering experience with support for voice input, menu browsing, upselling, and conversational responses — all in a sleek, real-time Streamlit app.

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.

MeetGist is an innovative meeting intelligence platform that revolutionizes how teams capture, process, and share meeting information. The application combines cutting-edge AI technologies with intuitive user experience to solve common challenges in meeting documentation and knowledge sharing. Key Features: Versatile Input Processing: Support for audio recordings (WAV/MP3), text transcripts, and synthetic meeting generation AI-Powered Summarization: Automatic extraction of key points, decisions, and action items using IBM Watson AI Smart Team Collaboration: Slack integration for automated sharing and interactive command support Comprehensive Dashboard: Centralized access to all meeting transcripts and summaries Technical Stack: Frontend: Streamlit for responsive user interface Backend: FastAPI for efficient API endpoints AI Integration: AssemblyAI for transcription, IBM Watson for summarization Database: Supabase for secure data storage Integration: Custom Slack bot implementation User Benefits: Time Savings: Reduce manual documentation effort through automation Improved Accuracy: Consistent and comprehensive meeting documentation Enhanced Accessibility: Easy search and retrieval of meeting content Better Team Alignment: Automatic sharing keeps stakeholders informed Flexible Usage: Multiple input options for different workflows MeetGist addresses the challenge of effective meeting documentation and knowledge sharing, making it essential for modern teams focused on productivity. Its combination of AI capabilities, user-friendly design, and integration features creates a complete solution for meeting intelligence management.

CardioCare is an AI-powered cardiovascular disease diagnosis and treatment recommendation system. It analyzes key health metrics such as body temperature, blood pressure, and cholesterol levels, along with medical reports (PDFs), to detect potential heart conditions early. Using DeepSeek AI, it provides personalized treatment plans, including diet, exercise, medication, and prevention tips. The system is designed to be affordable, accessible, and scalable, making advanced healthcare available to underserved communities. With a user-friendly interface and cloud-based deployment, CardioCare empowers individuals to take control of their heart health while reducing the burden on healthcare systems through early intervention and AI-driven insights.

AI Space Data Explorer 🌌🚀 AI Space Data Explorer is an advanced AI-powered platform designed to make space data more accessible and understandable for students, researchers, and space enthusiasts. Organizations like NASA and ESA generate vast amounts of data, but navigating and interpreting this information remains a challenge for the general public. Our solution leverages cutting-edge AI models and frameworks to simplify data retrieval, analysis, and visualization, making space insights more interactive and user-friendly. 🔹 Key Features: ✅ Conversational AI – Users can ask space-related questions and receive real-time insights from NASA and ESA datasets. Llama models, integrated via LangGraph and Groq API, ensure intelligent, context-aware responses. ✅ Smart Visualization – The AI transforms complex space data into intuitive graphs, charts, and reports, making it easier to analyze patterns and trends. ✅ Personalized Space Learning – The platform adapts to user preferences, recommending space topics, celestial events, and scientific discoveries based on individual interests. ✅ Seamless Data Retrieval – Using LangChain and NASA APIs, the system fetches and processes real-time space data, ensuring accuracy and relevance. ✅ Interactive Dashboard – Built with Streamlit, the user-friendly interface allows smooth interaction with AI-driven insights and visualizations. 🔧 Tech Stack & AI Models: Llama (via LangGraph & Groq API) – Powers intelligent Q&A interactions. LangChain + NASA APIs – Retrieves and processes real-time space data. Streamlit – Provides a sleek, interactive dashboard for exploration. 🎯 Impact: AI Space Data Explorer democratizes space knowledge, breaking down barriers to access and interpretation. By integrating AI-driven insights with real-time data visualization, the platform fosters curiosity, supports research, and enhances space education for all. 🚀

Project Description The Smart Financial Management Assistant is an AI-driven application designed to help users efficiently manage their personal finances. The system leverages machine learning algorithms and financial APIs to provide insights, budgeting assistance, and expense tracking. It also includes predictive analytics to forecast savings, expenses, and investments, empowering users to make informed financial decisions. Key Features Expense Tracking: Automatically categorize transactions using AI. Visualize spending patterns through charts and dashboards. Budget Management: Set financial goals and track progress in real time. Receive alerts for overspending or nearing budget limits. Investment Insights: AI-powered analysis of investment portfolios. Risk assessment and suggestions for portfolio improvement. Predictive Analytics: Forecast future expenses, savings, and income trends. Use AI to recommend strategies for achieving financial milestones. Smart Reminders and Notifications: Automatic bill reminders and payment tracking. Notifications for recurring subscriptions and unused services. Integration with Financial APIs: Securely connect to bank accounts and credit cards. Import real-time data for accurate financial analysis. AI-Powered Recommendations: Suggest cost-saving measures and investment opportunities. Provide financial literacy tips and guides.

We have developed a chatbot aimed at supporting individuals dealing with depression and mental health challenges in their daily lives. This innovative tool assists users in filtering messages, emails, and articles based on their emotional tone, enabling them to quickly determine whether the content warrants engagement without needing to read everything in detail. To enhance user comfort and trust, we incorporated color psychology in the chatbot’s design, choosing blue to symbolize trustworthiness. The chatbot also offers users the option to connect with a therapist if they desire further assistance. By analyzing the user's speech pace, the chatbot assesses emotional states—slower speech typically indicates sadness, while faster speech reflects happiness. This allows the chatbot to identify when a user may be experiencing depressive feelings. Additionally, the chatbot provides insights into the causes of these emotions and suggests possible solutions. Importantly, in cases where there is a risk of self-harm or serious mental health issues, it will always recommend speaking with a qualified professional. We believe that AI should not be solely relied upon for solutions to individuals struggling with depression, as this could breach ethical medical standards. Conversely, while there are no strict ethical guidelines limiting interactions with happy users, the chatbot acknowledges their positive emotions. It differentiates between happiness, anxiety, and anger by first checking speech pace and then analyzing specific words associated with these states. If a user is sad, the chatbot will use only one or two 'sad' emojis to build rapport, as excessive use can trigger negative emotions. In contrast, it enhances the experience for happy users by incorporating more 'happy' emojis to strengthen their connection.

AI-Powered Competitive Market Analysis is a sophisticated tool designed to provide businesses with critical insights into their competitive landscape, enabling them to make data-driven decisions and stay ahead of their competitors. By integrating artificial intelligence (AI) and machine learning (ML), this platform offers a comprehensive solution for monitoring competitors, analyzing market share distribution, and predicting future trends. Through the use of real-time data and advanced algorithms, it empowers companies to act strategically and proactively in an ever-changing market environment. Built on a user-friendly Streamlit front end and backed by the Together API, the platform ensures seamless and scalable functionality for businesses of all sizes. Streamlit is a key component of the platform's front-end, providing an intuitive and interactive user interface. Known for its simplicity and speed, Streamlit enables developers to create highly functional and visually appealing web applications with minimal code. For AI-Powered Competitive Market Analysis, Streamlit ensures that the user experience is seamless and customizable. The Together API powers the backend of AI-Powered Competitive Market Analysis, providing access to a wide range of data sources and machine learning models. The API is responsible for the platform's scalability and ensures that it can handle large volumes of data without compromising performance. AI-Powered Competitive Market Analysis is suitable for businesses of all sizes and across a variety of industries.

Grab your ideas, spin up compute, and start building what’s next! Start with $100 in AMD Developer Cloud credits and begin building right away. Get access to hands-on tutorials, workshops, and curated learning resources to help you build faster and go further. To unlock credits and join the hackathon, sign up for the AMD AI Developer Program. 🤝 Go solo or team up — ship something real. 💰 $21,500+ total prize pool & 1 × AMD Radeon™ AI PRO R9700 GPU up for grabs. 📍 On-site Venue (May 9-10): MindsDB SF AI Collective 3154 17th St, San Francisco, California, USA 📍On-site participation is by invitation only. Travel and accommodation expenses will not be covered. 🧑‍💻 Developers, builders, and innovators - bring your boldest ideas and let’s turn them into real AI systems on AMD.

⏱️ Design, build, and deploy trustless AI trading agents. 📅 March 30 – April 12, 2026 🌐 Build AI trading agents that execute strategies using ERC-8004 or Kraken CLI. 🤝 Build solo or in teams to create autonomous trading, risk, yield, or protection agents. 💰 $55,000 prize pool, allocated and shared via Surge and Kraken. Your team should have registered project at early.surge.xyz in order to be eligible for the prize. Get access in your team profile or our discord 🔑 Access to early.surge.xyz If prompted for login credentials, use: • Username: admin • Password: JBRv2xWG7AzwVrLz88

Join the next edition of our flagship AI hackathon — now featuring Google, AppliedAI, and Qdrant as official partners, with over $45,500 in prizes and exclusive partner challenges. After an incredible launch earlier this year, we’re back with the next edition of our AI hackathon series leading up to the /function1 AI Conference & Exhibition in Dubai. Tap into the power of AI to innovate, build, and take your AI skills to the next level in this high-impact hybrid experience. 📅November 14–19, 2025 • Nov 14–18: Collaborate and build online with AI enthusiasts from around the world. All projects must be submitted by end of day on November 18 • Nov 18 (Dubai): An exclusive on-site build day at Festival Arena Dubai for selected participants. • Nov 19 (Dubai): Live on-stage pitching & winners announcement at the /function1 Conference. 🌟 Get support from expert mentors throughout. 👥 Go solo or team up. 📍 Please note: On-site participation is by invitation only. Travel and accommodation will not be covered for selected participants. Further details will be shared with those accepted. 🧑🏻‍💻 Secure your spot now—sign up before the Kick-Off Stream!

In this hybrid hackathon powered by Arc, developers will build the next generation of payment systems using AI + Arc with USDC. Explore a world where AI agents can understand natural language, automate financial actions, and move money with precision. From DeFi to digital content and real-world assets, this is your chance to shape the future of intelligent finance. 📅 October 27 – November 9, 2025 • Oct 27 – Nov 8 (Online Phase) – Collaborate and build with developers and AI innovators from around the world. All projects must be submitted by end of day on November 8. • Nov 8 (New York City – On-site Build Day) – Selected participants will be invited to an exclusive in-person session to refine their projects and connect directly. • Nov 9 (New York City – Live pitching & Awards) – Live pitching sessions to a panel of judges and investors, followed by the official winner announcement. 📍 On-site Venue (Nov 8–9): Babe Ruth Room, Jay Conference Chelsea 159 West 25th Street, New York City, USA 🧠 Get guidance from blockchain and AI experts throughout the event. 🤝 Go solo or team up — it's your flow. 🏆Compete for $10,000 in USDC prizes. 📍 On-site participation is by invitation only. Travel and accommodation expenses will not be covered. 🧑🏻‍💻 Secure your spot now — sign up before the Kick-Off Stream!