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.

### **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 ✅ Reduces risk by avoiding investment in outdated features.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!**

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.