Pavantej Veesam's Projects
Eco_Veta company website
The "Electives Management" project aims to simplify the process of choosing elective subjects for students in engineering or other degree programs. Traditionally, colleges and universities rely on a lot of paperwork and manual processes for elective selection, which can be cumbersome and time-consuming for both students and administration.
It's an IOT based project were our motive to enhance the security measures in ATM's to prevent them from the theft
An analysis tool that automates the process of data extraction, cleaning, analysis, and visualization. This tool is built using Python and Streamlit, providing an intuitive web interface for users to upload datasets and receive comprehensive analysis and visualizations.
This project aims to simplify the process of analyzing datasets using SQL queries. Users can upload their datasets in CSV format, input their desired SQL prompt, and our API will generate the query and display the output accordingly.
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MELA is a groundbreaking application designed to eliminate language barriers in emergency medical situations. When a user is involved in an accident, MELA facilitates seamless communication with ambulance services and hospital management in the user's regional language.
NOVA is an AI-based home automation project, featuring our custom Nova Voice Assistant designed to provide personalized assistance.
Nova Voice Assistant is a simple Python-based virtual assistant that can perform various tasks through voice commands. It utilizes speech recognition and text-to-speech capabilities to interact with users.
I have built a patent search application that lets users search an idea or topic in a patent database (made publicly available in BigQuery) for published patents that closely match their topic or context of search using Similarity Vector Search in Spanner.
The system utilizes Natural Language Processing (NLP) techniques to analyze patient data and drug information.
This repository contains the results of a process mining project conducted as part of an Eduskills Techcamp workshop. The project utilized Celonis to analyze a pizza shop's event log data with the aim of identifying process inefficiencies and potential optimization opportunities.