Our project is an AI-powered compliance analysis system that leverages Coral v1 and the Mistral AI API to evaluate GitHub repositories for domain-specific rules and regulations. The system is designed with a modular architecture consisting of a frontend, backend, and intelligent agents that work together seamlessly. The frontend allows users to input a GitHub repository URL, which is then processed by the backend and routed to specialized agents. These agents, in collaboration with the Fire-Crawl agent, extract the repository’s structure, metadata, and domain-relevant information. The results are compiled into a detailed compliance report, ensuring accuracy, efficiency, and adaptability across various domains.

One of the biggest challenges in modern research is dealing with information overload. Analysts, researchers, and organizations often need to process vast amounts of unstructured data—ranging from academic papers and PDFs to dynamic web content. Manually filtering, extracting, and validating insights is time-consuming, prone to bias, and difficult to scale. Our project addresses this gap by building a mini AI research lab, a system that combines retrieval, structured extraction, experimentation, and judgment. At its core, we use GPT-5 efficiently as a multi-role reasoning agent rather than just a conversational assistant. For example, GPT-5 powers the Extractor, transforming raw text into structured evidence with minimal noise. The Experimenter module leverages GPT-5 to simulate hypotheses, cross-check facts, and test consistency across different sources. Finally, the Judge role allows GPT-5 to evaluate credibility, logical soundness, and contextual relevance—acting as a safeguard against misinformation. By integrating GPT-5 with hybrid retrieval (FAISS + BM25), we ensure precise context delivery while minimizing token usage. This efficient workflow solves a real-world problem: enabling faster, more reliable, and scalable knowledge discovery.

OpsPilot is designed to enhance productivity and communication for professionals by leveraging AI and automation. It acts as a personal assistant for email management and scheduling, reducing the time spent on administrative tasks. Through intelligent integrations with services such as Google Calendar, Gmail, and Coral Protocol, OpsPilot assists with scheduling meetings, providing AI-powered summaries, managing inboxes, and offering insightful reports. Users can rely on OpsPilot to suggest optimal meeting times based on calendar routines, send follow-up emails, and offer smart suggestions to enhance work efficiency.

Auto-DevOps Agent is an AI-powered automation system designed to simplify and accelerate the setup of CI/CD pipelines for developers. Built for hackathons and real-world projects alike, it leverages a multi-agent architecture where each agent performs a specific DevOps task—detecting the tech stack, generating test/build/deploy steps, and combining them into a valid GitHub Actions YAML workflow. It also provides easy-to-understand explanations for each CI/CD step, enabling developers to learn while automating. The system supports various project types such as Python, Node.js, and Java, and is designed to eliminate the manual, error-prone work often required when configuring CI/CD tools. The agents communicate using structured prompts and are powered by LLMs via the Groq-hosted OpenAI SDK using the LLaMA 3.1-8B model. The full stack includes: Frontend: React.js (for user interaction and input handling) Backend: FastAPI (serving the AI agents and managing request logic) Agents: AI multi-agent system using prompt engineering and OpenAI SDK CI/CD Output: GitHub Actions YAML configuration Optional Extensions: Docker, GitHub Secrets, and platform deployment integrations The current version generates test, build, and deploy pipeline steps. Future enhancements will include direct deployment to platforms like Railway, Streamlit, Vercel, and Render, along with automated GitHub secret management and full repository initialization. This makes Auto-DevOps Agent an ideal solution for developers, students, and teams aiming to streamline DevOps without needing deep YAML or DevOps knowledge.

### **AI-Powered Reverse Engineering Assistant** Businesses struggle to stay ahead due to long R&D cycles, high costs, and limited competitor insights. Our AI-powered reverse Engineering Assistant leverages IBM Granite AI and NLP to automate benchmarking, feature extraction, and innovation scoring, helping companies make data-driven decisions faster. ### **Key Features** #### 🔍 **Competitor Product Analysis** - Extracts specs, features, pricing, and feedback from manuals, reviews, patents, and datasheets. - Uses AI to highlight strengths, weaknesses, and innovation gaps. #### 📊 **AI-Powered Benchmarking** - Compares user products against competitors to find areas for improvement. - Analyzes key components, pricing strategies, and market trends. #### ⚙️ **Faster R&D Through Reverse Engineering** - Speeds up product development by analyzing competitors in real time. - Reduces trial-and-error with AI-driven prototyping insights. - Ensures compliance by focusing on publicly available data. ### **Industries That Benefit** ✅ **Consumer Electronics**: Smartphones, laptops, smart devices. ✅ **Automotive**: Vehicle features, safety, energy efficiency. ✅ **Pharmaceuticals**: Drug formulations, medical devices. ✅ **Manufacturing**: Machinery, production techniques. ✅ **Software & SaaS**: AI models, cloud platforms, enterprise apps. ### **Business Impact** ✅ Cuts R&D time by **50%**, accelerating innovation. ✅ Saves costs by providing **ready-to-use insights**. ✅ Enhances market competitiveness by aligning with trends. ✅ Reduces risk by avoiding investment in outdated features. ### **Conclusion** The AI-powered reverse Engineering Assistant helps businesses **innovate smarter** and outperform competitors. By integrating **IBM Granite AI**, it **automates competitor analysis**, making R&D **faster, smarter, and more cost-effective**. **Revolutionizing R&D with AI!**

Our project is an AI-driven assistant built using React, Python, and DeepSeek Groq API, featuring 7 specialized agents to enhance users' professional and personal lives. These agents include a Business Analyst for market insights, a Health Analyst for medical advice, and a News Fetcher for real-time updates on selected topics. The system empowers users by providing expert-driven insights, enabling informed decision-making in business, healthcare, and current affairs. Designed for efficiency, it ensures users stay ahead with crucial information, making it a valuable tool for entrepreneurs, professionals, and individuals seeking reliable, AI-powered guidance in their daily activities.

Create noteworthy apps with advanced reasoning across audio, vision, and text in real time with GPT-4o. 🕒 72 hours to complete the challenge 💡 Create revolutionary apps which use GPT-4o advanced features 🤝 Take part alone or form a team with other participants 🚀 Engage in a 3-day virtual development marathon and network with tech and business leaders 🏆 Win opportunity to participate in LabLab NEXT acceleration program

🕒 15 days to complete the challenge. It's an amazing opportunity to: 🌟 Explore new AI capabilities 🤝 Collaborate and build something extraordinary. 👥 Take part alone or form a team with other participants. 🎓 Receive guidance from expert mentors. 🏆 Compete for $32,500 in Prizes and a Full-Time Job Opportunity! 🎓 Exclusive job offers for top participants. 🧑🏻‍💻 Sign up before the Kick-Off Stream to secure your spot!

Create your product using Codestral, Mistral's first-ever open-weight generative AI model for code generation. 🕒 24 hours to complete the challenge. 💡 Implement any idea that uses Codestral at its core. 🤝 Take part alone or form a team with other participants. 🏆 Win an opportunity to participate in LabLab NEXT acceleration program