Software Developer +
DevOps Engineer
I specialize in designing and building robust, scalable web applications using Python, Django, and React JS. With a strong foundation in database design and RESTful API development, I create efficient and secure solutions tailored to business needs. I'm passionate about DevOps, focusing on automation, continuous integration, and seamless cloud deployments.
My Recent Works
Explore some of my recent projects showcasing backend development, cloud infrastructure, and DevOps automation.
Docuverify: Plagiarism & AI Detection
Docuverify is a comprehensive alternative for Turnitin, it is a plagiarism and AI detection platform built using Django, Django REST Framework, and React JS. It empowers users to efficiently manage their documents and detect potential plagiarism or AI-generated content. The platform automates critical functions, including tracking document versions, generating reports, and providing alerts, ensuring a seamless experience for users.
Users can submit their documents for analysis and receive detailed feedback on potential issues. The platform also integrates with popular document management systems, making it easy to incorporate into existing workflows.
Smart Route Optimizer
Smart Route optimizer is a real time route optimization tool that provides real time traffic, weather, and road condition updates to help users find the best routes for their journeys.
Users can submit their routes for analysis and receive detailed feedback on potential issues. The platform also integrates with popular mapping systems, google places, mapbox, google directions and a custom AI layer to provide real time updates on traffic, weather, and road conditions.
clavaChat Marketplace
ClavaChat is an innovative WhatsApp chatbot marketplace designed to facilitate seamless buying, selling, leasing, and renting of properties. As the lead developer, I set up and managed a robust AWS infrastructure, ensuring high availability and scalability for the chatbot. This platform not only empowers users to manage their listings efficiently but also features a library section where users can search for and download books effortlessly.
By integrating a local payment system, clavaChat allows sellers and landlords to subscribe and manage their listings effectively. This project has significantly enhanced my skills in handling server loads and balancing user requests with available resources, motivating me to continue innovating in the field.
pipelines
Using Github actions, lambda functions, and other AWS services, I built a robust CI/CD pipeline for a web application.
This pipeline automates the deployment process, ensuring that code changes are tested and deployed efficiently. It integrates with various AWS services to provide a seamless deployment experience, enhancing the overall development workflow and automatic rollbacks in case of failures.
Lost & Found
Users can easily post lost or found items, either through the WhatsApp chatbot or via the website. You can set alerts for lost items that haven't been found yet. Keep track of important details like location, date, and category to quickly find what you're looking for.
Xira - Customer support system
Developed a customer support system built with Django, utilizing GitHub Actions for CI/CD. The application is hosted on AWS and allows users to open inquiries through various channels, including web, WhatsApp, and email. All support interactions are managed via a WhatsApp chatbot or the web interface, ensuring that replies reach the original inquirer. The system also tracks all activities for comprehensive reporting and analysis, enhancing overall support efficiency.
Docuverify: Plagiarism & AI Detection
Built using Django, Django REST Framework, and React JS, Docuverify is a comprehensive platform for detecting plagiarism and AI-generated content in documents.
Project Description
Docuverify is a powerful plagiarism and AI detection platform designed to help users manage their documents effectively. The platform automates critical functions such as tracking document versions, generating reports, and providing alerts, ensuring a seamless user experience.
Users can submit their documents to their supervisors for analysis, and the platform sends the student a detailed email on potential plagiarism or AI-generated content. The integration with popular document management systems allows for easy incorporation into existing workflows.
The frontend is developed with React JS, typescript ensuring a seamless user experience for managing documents and reviewing analysis results.
TFIDF (Term Frequency-Inverse Document Frequency) is a statistical measure used to evaluate the importance of a word in a document relative to a collection of documents (corpus). In the context of Docuverify, TFIDF can be employed to analyze the content of submitted documents and identify key terms and phrases that may indicate potential plagiarism or AI-generated content.The TFIDF algorithm works by calculating the frequency of each term in a document and comparing it to its frequency across the entire corpus. This helps in identifying unique terms that are more likely to be plagiarized or generated by AI, as they may not appear frequently in other documents.
Roberta is a transformer-based model that can be used for various natural language processing tasks, including text classification and content analysis. In the context of Docuverify, Roberta was utilized to enhance the accuracy of plagiarism detection and AI content identification.
The Story
The idea for Docuverify emerged from the need for a comprehensive free, self-hosted solution to detect plagiarism and AI-generated content in academic and professional documents. The platform aims to provide users with an efficient way to manage their documents while ensuring the integrity of their work.
Approach
By using Django and Django REST Framework for the backend, I created a robust API that handles document submission, analysis, and reporting. The React JS frontend provides an intuitive interface for users to manage their documents and review analysis results.
Project Description
Smart Route Optimizer is a real-time route optimization tool that provides users with the best routes for their journeys, considering traffic, weather, and road conditions. The platform allows users to submit their routes for analysis and receive detailed feedback on potential issues.
The platform integrates with popular mapping systems such as Google Places, Mapbox, and Google Directions, along with a custom AI layer to provide real-time updates on traffic, weather, and road conditions. This ensures that users can make informed decisions about their routes and avoid potential delays.
Tech stack: Django, DRF, React JS, typescript, Google Maps API, Mapbox API, OpenWeatherMap API.
calculating the best route involves analyzing various factors such as distance, traffic conditions, and estimated travel time. The platform uses advanced algorithms to determine the most efficient route based on real-time data.
The Story
The idea for Smart Route Optimizer was born out of the need for a reliable and efficient route optimization tool that could provide real-time updates on traffic, weather, and road conditions. The platform aims to help local users find the best routes for their journeys, ensuring a smooth and hassle-free travel experience while taking into account their specific needs and preferences and also giving them precise info about fuel consumption, weather conditions for the destination at expected arrival time, alternative routes, and estimated arrival times.
Approach
By using Django and Django REST Framework for the backend, I created a robust API that handles route submission, analysis, and reporting. The React JS frontend provides an intuitive interface for users to manage their routes and review analysis results.
WhatsApp Chatbot Marketplace
A Flask-based WhatsApp chatbot serving as a marketplace for buying, selling, and leasing properties, along with a library section for seamless book downloads.
Project Description
The WhatsApp chatbot marketplace allows users to buy, sell, lease, and rent properties. It features a library section where users can search and download books seamlessly.
The chatbot was built using Flask and hosted on Render, incorporating a local payment system for sellers and landlords to manage their listings.
The Story
This project was my first to be launched for many users, motivating me to innovate and learn about server loads and resource management.
Approach
I utilized Flask to build the chatbot, ensuring a smooth user experience. The integration of a local payment system allowed for efficient management of listings by sellers and landlords.
Lost and Found Platform
Developed a comprehensive Lost and Found platform using Django, enabling users to recover lost items or post lost and found items seamlessly.
Project Description
The Lost and Found platform enables users to post or search for lost items via a WhatsApp chatbot or web app. If a user searches for an item that is not found, Celery continuously checks for matches with newly posted items.
Once a match is found, the system alerts the assumed owner, initiating the verification process. Users can also track their activities, including items they have lost or found, and manage their postings effectively.
The Story
Recognizing the need for a streamlined process to recover lost items, we developed a user-friendly platform that allows users to report and track lost and found items efficiently. The integration of a WhatsApp chatbot enhances user engagement and accessibility.
Approach
Leveraging Django for backend development, we created a robust architecture that supports real-time updates and notifications. The use of Celery for asynchronous task management ensures users are promptly alerted when matches for their lost items are found, enhancing the overall user experience.
XIRA - Customer Support System
XIRA is a comprehensive customer support system built on Django and deployed on AWS. The platform leverages Docker for containerization, enabling efficient and scalable deployment processes. It allows users to open inquiries through various channels, including WhatsApp, web applications, and email. Support members can seamlessly assist users via WhatsApp, with all interactions recorded for reporting and analysis.
Project Description
XIRA is designed to facilitate efficient communication between users and support staff. Users can open inquiries through their preferred method, while support members can respond via WhatsApp. The system's APIs handle the secure exchange of messages, ensuring that all correspondence is delivered to the appropriate recipient.
All interactions are recorded for compliance, reporting, and analysis, providing valuable insights into support activities and performance metrics.
The Story
In response to the growing need for an integrated customer support system, XIRA was developed to bridge communication gaps. The platform allows inquiries to be opened through multiple channels, ensuring users can receive timely assistance.
Approach
Utilizing Django and AWS, I designed XIRA to support multiple inquiry channels, ensuring a seamless experience for users and support members. The system was built with a focus on security and scalability, allowing for efficient handling of user inquiries and the recording of support activities.
My Skills & Tech Stack
As a DevOps Engineer my goal is to leverage my skills in automation and infrastructure management to enhance deployment processes and drive operational efficiency.
Django
AWS
Docker
Flask
Redis
Terraform
Git
React
PostgreSQL
Let’s Collaborate
I am eager to engage in innovative projects and strategic collaborations. Let's explore how we can achieve remarkable results together.
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Phone
+263 779586059 -
Email
gtkandeya@mail.com -
Address
Harare,
Zimbabwe