ARYAN KUMAR RAI

Key Features:

• Configured Clerk for secure user authentication, enabling streamlined onboarding, access control, and persistent user sessions.
• Adopted Convex to power real-time data update, seamless storage management, and serverless logic-all without maintaining traditional backend services.
• Implemented AI workflows using Vapi and the Gemini API to dynamically generate personalized diet and workout plans based on user input and goals.

User Flow:

1. User authenticates securely through Clerk's streamlined authentication system.
2. User initiates an interactive session with the voice assistant.
3. The VAPI voice assistant communicates with dedicated API endpoints to request personalized diet and workout plans from Gemini.
4. Gemini intelligently generates comprehensive programs within the Convex backend environment.
5. VAPI retrieves the tailored data from Convex and elegantly arranges it in the appropriate interface sections.

Key Features:

• Integrated Clerk for secure user authentication and account management, including support for sign-up/sign-in flows and user session handling.
• Utilized Convex as a backend-as-a-service to handle real-time data syncing, storage, and serverless functions without managing infrastructure.
• Implemented LemonSqueezy payment integration to handle subscription billing and enabled gated access to Pro plan features for premium users.

User Flow:

1. Users access the code editor workspace via Clerk's secure authentication, providing a frictionless entry point to the development environment.
2. Developers leverage our feature-rich code editor to write, test, and optimize their code snippets with real-time syntax highlighting and intelligent suggestions.
3. The platform integrates with Piston's execution engine to run code in a sandboxed environment, delivering validation results directly in the interface.
4. All code snippets are automatically versioned and stored in our Convex database, creating a searchable library of solutions accessible across devices.
5. Unlockable advanced collaboration features through our Lemon Squeezy payment gateway, enabling snippet sharing, and, commenting.

Key Features:

• Engineered an LLM-powered scheduling agent using LangGraph to autonomously handle meeting requests with natural language processing.
• Built a FastAPI backend integrated with Gemini API for intelligent scheduling and conflict resolution.
• Developed a Streamlit dashboard for real-time monitoring, debugging, and user interaction analytics

User Flow:

1. User accesses the Streamlit dashboard.
2. User submits a meeting request or scheduling query in natural language.
3. The request is sent to the FastAPI backend, which processes the input and interacts with the Gemini API for intelligent scheduling and conflict resolution.
4. LangGraph orchestrates the LLM workflow, parsing intent, extracting entities (like date, time, participants), and managing conversation state.
5. The backend checks for conflicts, suggests optimal meeting times, and updates the schedule accordingly.
6. The Streamlit dashboard displays the scheduling outcome, provides real-time feedback, and logs analytics for user interactions.

Key Features:

• Integrated Gemini API for intelligent, context-aware evaluation of text-based submissions.
• Developed a modern, responsive user interface using React, Tailwind CSS, and Framer Motion for smooth animations and an engaging user experience.

User Flow:

1. User fills out and submits the evaluation text on the React frontend.
2. Backend receives the input, processes it through the Gemini API, and answer it contextually.
3. User views the report directly from the interface.