TanyAI

Tanya Thomas

ASP.NET Core & Cloud Developer

Building secure, scalable business applications with ASP.NET Core, Entity Framework, SQL Server, and AWS cloud technologies.

GitHub

About Me

I am a software developer focused on building secure and scalable business applications using ASP.NET Core, C#, SQL Server, and cloud technologies. My projects emphasize clean architecture, role-based authorization, responsive UI design, and practical real-world workflows.

I enjoy designing systems that combine strong backend functionality with intuitive user experiences, while continuing to expand my skills in cloud computing, AI integrations, and enterprise application development.

AWS

GenAI

SQL

JSON

C++

My Portfolio

Angelique Solis

Angelique Solis is an example of a responsive modeling portfolio website designed to showcase the work and personal brand of a professional model. Built with HTML, CSS, and JavaScript, the site features a clean, accessible layout with dedicated sections for photoshoots, film work, digital media, and booking inquiries. It includes a custom contact form with validation, consistent branding throughout, and a navigation structure optimized for all screen sizes. The project demonstrates front-end development skills, visual design, and attention to user experience, and is deployed via GitHub Pages.

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Pet Connect Management System

PetConnect is a full-stack ASP.NET Core MVC application designed to manage animal shelters, adoptions, adopters, payments, and staff operations. The system features role-based authorization, Clean Architecture principles, Entity Framework Core, SQL Server integration, and comprehensive manual QA testing documentation.

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AWS Appointment System

AWS Appointment System is a fully serverless cloud-based application designed to automate appointment scheduling, confirmations, and notifications. Built using core AWS services, the system uses Amazon Lex to collect appointment details through conversational input, AWS Lambda for processing logic, DynamoDB for persistent storage, and Amazon SNS/SES to send SMS and email confirmations. Upon successful booking, users receive a message with a secure token and a link to a phone or video meeting. This project demonstrates the integration of multiple AWS services to deliver a real-time, scalable, and cost-efficient solution for managing appointments without traditional infrastructure.

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AWS Ground Station Data Delivery

AWS Ground Station S3 Data Delivery is a reference architecture demonstrating how to automate the delivery of satellite data directly into Amazon S3 using AWS Ground Station. This solution leverages event-driven architecture to streamline data workflows from satellite passes to cloud storage, using services like Amazon EventBridge, Lambda, and Step Functions. It provides a scalable and cost-efficient method to downlink, process, and store satellite data for further analysis or machine learning workloads. The project showcases how AWS enables real-time space-to-cloud data delivery without the need to manage ground infrastructure.

AWS-Based Image Recognition System

AWS-Based Image Recognition System is a cloud-native application that performs basic image classification using Amazon Rekognition. Designed to demonstrate how artificial intelligence can be integrated into modern serverless workflows, this project allows users to upload images through an S3 bucket, which then triggers a Lambda function to analyze the image content. Amazon Rekognition detects and labels objects, scenes, or concepts, and the results can be logged or used for further automation. This project showcases how to leverage managed AI services within AWS to create scalable, event-driven image processing pipelines without the need to train your own models.

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