**CareSync Nexus** is an AI-powered family healthcare management platform designed to simplify and modernize healthcare coordination for patients, caregivers, and healthcare providers. The platform addresses critical challenges such as missed medications, fragmented medical records, limited caregiver visibility, and delayed access to healthcare services. Using AI-powered prescription scanning and medical report analysis, CareSync Nexus automatically identifies medications, creates personalized medication schedules, and generates intelligent reminders. The platform enables caregivers to monitor their loved ones in real time through a comprehensive health dashboard featuring medication adherence, vital signs, AI-generated health summaries, and emergency alerts. Beyond medication management, CareSync Nexus integrates doctor appointment booking, nearby hospital discovery, video consultations, ambulance services, wearable device synchronization, multilingual AI chatbot support, and predictive health risk alerts into one connected ecosystem. Patients receive personalized health guidance, dietary recommendations, and follow-up wellness check-ins, while caregivers are instantly notified if medications are missed or abnormal health conditions are detected. By bringing together AI, healthcare, and connected family care, CareSync Nexus transforms fragmented healthcare into a proactive, data-driven, and collaborative experience. The vision is to build a unified healthcare ecosystem that improves medication adherence, enhances patient outcomes, reduces caregiver anxiety, and makes quality healthcare more accessible for every family.

Developed an AI-powered FAQ chatbot automation system using n8n, Google Sheets, and OpenAI to provide automated, contextual, and real-time responses to user queries through a website chatbot interface. The project uses a RAG (Retrieval-Augmented Generation) architecture where chatbot responses are dynamically generated based on FAQ data stored in a single Google Sheet. The system retrieves the most relevant FAQ information and augments AI-generated responses for accurate and human-like customer support interactions. Key Objectives Automate repetitive customer support queries Reduce manual response handling Create a scalable AI FAQ assistant Enable non-technical teams to manage FAQs easily Integrate chatbot with website frontend

**Linux-Based AI Agent for Intelligent System Administration** is an AI-powered web application developed using Python, Flask, Linux system utilities, and the OpenAI API to simplify Linux system administration through natural language interaction. The project provides an intelligent AI terminal assistant where users can execute Linux commands, monitor system processes, retrieve hardware information, and receive explanations for complex terminal commands using simple conversational queries instead of memorizing difficult command-line syntax. Traditional Linux administration can be challenging for beginners and time-consuming for administrators due to the need for extensive command knowledge, troubleshooting skills, and manual operations. This project addresses these issues by integrating artificial intelligence with Linux automation, enabling users to interact with the system more efficiently and intuitively. The AI agent improves productivity by reducing manual effort, assisting in command understanding, and automating administrative tasks through a user-friendly web interface. The system acts as a bridge between human language and Linux system operations, making Linux management more accessible, interactive, and efficient for both learning and real-world administration tasks.

1) RAG Pipeline & Chatbot ## First I choose a trigger name is Google Drive Trigger and connected to the https://console.cloud.google.com/ and enable google API Key. ## Second I attached a seond trigger which is Download File, and attach json ID ## Third Create an Pinecone Database connect with the nodes and generate API key and create index that connected with the Embedding Open AI Model that helps me to chunk the data.

1) RAG Pipeline & Chatbot ## First I choose a trigger name is Google Drive Trigger and connected to the https://console.cloud.google.com/ and enable google API Key. ## Second I attached a seond trigger which is Download File, and attach json ID ## Third Create an Pinecone Database connect with the nodes and generate API key and create index that connected with the Embedding Open AI Model that helps me to chunk the data.

1) RAG Pipeline & Chatbot ## First I choose a trigger name is Google Drive Trigger and connected to the https://console.cloud.google.com/ and enable google API Key. ## Second I attached a seond trigger which is Download File, and attach json ID ## Third Create an Pinecone Database connect with the nodes and generate API key and create index that connected with the Embedding Open AI Model that helps me to chunk the data.

The application compares user's uploaded resume with the given job description and gives the ATS matching score. It displays a score, the candidate's strengths and missing skills and tools.

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An application that helps people to have basic knowledge of investment. As peopl are starting to invest more but still making loss. So used ai to make working ai tool for this and prototype.

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