Ryan Montville
Full-Stack Developer | Dynamic apps & secure databases
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Ryan is ready for their next project!
Full-stack website for a non-profit built with TypeScript, Vite, and HTML/CSS. Deployed on Cloudflare Pages for fast, edge-network performance with Firebase handling real-time data and auth.
Key Deliverables: • Integrated Givebutter to handle secure donor management and payment processing. • Built a secure photo upload pipeline utilizing Cloudflare R2 object storage. • Developed a custom rich-text editor using Quill.js, empowering non-technical staff to update content seamlessly.
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Bilingual inventory & event management app built with TypeScript, Vite, Cloudflare Pages, and Firebase, featuring full English/Spanish localization.
Key Features: • Inventory & Reports: Streamlined stock tracking with real-time reporting tools. • Event Logistics: Custom module for scheduling events and volunteer sign-ups. • Donor Engagement: Project portal demonstrating donor impact, plus mailing list sign-ups.
Delivered a secure, high-performance serverless solution that completely automates daily operations across two languages.
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Data-processing and visualization platform that parses database log files from an annual collaborative pixel art event into interactive analytics. Turned raw event logs into an engaging, high-performance data platform.
Key Features: • Advanced Visualization: Uses D3.js to render complex trend graphs and interactive statistical charts. • Dynamic Image Generation: Leverages HTML Canvas to reconstruct and render custom artwork segments. • Analytics & Search: Generates granular user rankings, server participation metrics, and overall canvas stats with robust search functionality.
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Mobile web app built with TypeScript, HTML/CSS, and Firebase to streamline apiary management and beehive health tracking.
Key Features: • Field-Optimized UI: Tailored layout designed with high-contrast, oversized touch targets for seamless data entry while wearing thick beekeeping suits. • Historical Logging: Fast inspection logging, notes, and interactive hive health visualizations. • Predictive Analytics: Aggregates historical inspection data to identify trends and predict future hive events (e.g., swarming).
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