Manas Vajpayee

MethaneGuard AI '26

Brand & Creative Builder Award '26

it is project

Student Expense Tracker

This project is a command-line Student Expense Tracker built entirely in Python using only the standard library, with no Django, Flask, or any web framework, and no database — all data is stored in memory using Python lists and dictionaries, exactly as required. It fully implements all four core requirements: users can add an expense with date, amount, and category (food, travel, recharge, or other); view all expenses in a clean tabular format; see the total amount spent at any time; and see which category has the highest spending, backed by a visual bar chart. As a bonus feature, the program also lets users set a monthly budget and automatically shows a color-coded warning when spending crosses that budget, along with a usage percentage and remaining balance. To satisfy the requirement that reviewers see output immediately, the program pre-loads five sample expenses across all four categories along with a sample ₹1,000 budget, and prints a complete report the instant it is run, before any menu or user input is needed. Beyond meeting the base requirements, the tool is designed to feel like a real application rather than a plain script: it has a colored dashboard, category icons, screen refreshes between actions, and progress bars, while still degrading gracefully (colors and clearing disabled) when run in a non-interactive or piped environment, which was verified through syntax compilation checks, a no-input run, and a full simulated menu-walkthrough — all completing with zero errors and a clean exit.

EXPIRY ALERT ' 26

Large enterprises (Deloitte, Tata Steel, Adani, JSW, Vedanta, Reliance-type organizations) manage hundreds of time-sensitive documents — vendor contracts, compliance certificates, safety records, insurance policies, inspection reports, and licenses. These are typically tracked in scattered spreadsheets and emails, leading to missed renewals, penalties, and audit failures. Horizon solves this by giving a single, real-time view of what's active, expiring, or expired. Core functionality delivered: Dashboard-first design — KPI tiles (Total / Active / Expiring / Expired) give an instant status snapshot, clickable to filter the register below. "90-Day Runway" visualization — a signature timeline plotting every record relative to today, color-coded by urgency, so risk is visible at a glance rather than buried in rows. Full record lifecycle — Add, Edit, Renew (one click extends expiry and logs the previous date), and Delete, with form validation. Filtering & search — by category, status, and free-text search across name/vendor/reference number; sortable by urgency. Urgency flagging — records expiring within 7 days or already expired are visually flagged as needing immediate action. Data persistence — records are saved across sessions, with a sample dataset (seeded with realistic entries) to demo instantly. Responsive UI — usable on both desktop and mobile, with a professional, distinct visual identity rather than a generic template. Strengths: Directly maps to the stated goal — it's a monitoring/alerting layer, not a document storage platform. Visual design (navy + brass palette, IBM Plex typography) feels enterprise-grade and purpose-built, not a generic dashboard template. The runway visualization is a genuinely differentiated way to communicate "staying ahead of expiry," which ties the UI back to the problem statement. Areas for future iteration (good to mention proactively in a pitch): Email/WhatsApp/SMS reminder automation ahead of expiry (currently visual-only, no push notifications). Role-based access and multi-organization/multi-site support for larger enterprise rollout. Document file attachment/upload alongside metadata (currently tracks metadata, not the file itself — intentional, per the brief's scope). Audit trail/history log per record for compliance traceability. CSV/Excel bulk import and export for migrating existing spreadsheet data

CareQ – Live Clinic Queue Manager

Small and neighborhood clinics still rely on paper tokens and manual queue management, causing long waiting times, poor visibility, and repeated inquiries from patients. There is no simple way for patients to know their position in the queue or estimated waiting time. CareQ solves this problem by providing a real-time digital queue management system that improves transparency, efficiency, and patient experience. Process I started by analyzing common challenges faced by small clinics, such as manual token distribution, patient confusion, and lack of real-time updates. Based on these findings, I designed a dual-interface system consisting of a Receptionist Dashboard and a Patient View. The solution was built around real-time synchronization using Socket.io, ensuring that queue updates are reflected instantly on patient screens. MongoDB was used to store queue data, while React and Node.js were chosen to provide a scalable and user-friendly experience. Results The solution successfully digitizes clinic queue management by replacing paper-based tokens with a real-time system. Patients can view their queue status, current serving token, and estimated waiting time instantly. Receptionists can manage the entire queue from a single dashboard, reducing manual effort and improving operational efficiency. The system provides a more transparent and organized experience for both patients and clinic staff. Reflection In future versions, I would integrate AI-powered wait time prediction, SMS notifications, multi-doctor queue support, and appointment scheduling features. I would also conduct real-world testing in clinics to gather user feedback and further optimize the system for large-scale deployment

IPL Crunch 26 - ANALYTICS DASHBOARD

Analyzed IPL data to identify match-winning patterns using statistics and visual analytics. Process Cleaned IPL datasets, performed analysis, and built a dashboard using Python and Matplotlib. Results Discovered that middle overs impact winning more than toss advantage. Reflection Would add interactive filters and team-wise comparisons for deeper insights.