Portfolio - Products shipped and maintained

Every serious product needs the same first layer: identity, data, billing, email, uploads, analytics, authorization, and a deployment path. I rebuilt that layer often enough to learn which abstractions survive and which ones get in the way.

Draupnir keeps those decisions in one working application. It is the starting point I now use when a product needs to become real, and it is now available to other developers.

Promad is my own take on a home base for professional nomads: people who work remotely as a career choice, not a gap year. It is a community rather than a magazine, funded partly by affiliate links on the destinations and gear I actually recommend, plus a newsletter for anyone not ready to join outright. I haven't picked the platform yet. Discord, Telegram, and Slack are all still on the table.

It's early and I'm building it in the open. Six destinations and six gear picks live so far, two essays published, more added as I actually use and vet them. Next.js, TypeScript, Drizzle, and Velite sit under the hood. Content and affiliate links come first, followed by the community layer once the platform choice is locked in.

Towers Club catalogs over 100 iconic residential skyscrapers across 25+ global cities, featuring 50+ world-renowned architects. From Manhattan supertalls to Oslo landmarks, the platform lets architecture enthusiasts explore, compare, and build personal collections.

Built on Lovable as a rapid prototype, Towers Club demonstrates how curated vertical directories can create engaged communities around niche interests. Here, that interest is the intersection of real estate, architecture, and urban living.

Homi is an AI-powered home search platform that transforms how people find their next place to live. Instead of endless scrolling through listings, users have natural conversations with AI to discover homes that truly match their needs.

I built Homi on a modern tech stack: Next.js, TypeScript, and tRPC. The platform launched with 250+ organic signups, secured broker pilots, and achieved first MRR within months of launch.

SwipeStats is a dating data analytics platform that helps people understand their dating app behavior through data. Users upload their Tinder data anonymously and receive detailed visualizations and insights about their patterns, preferences, and performance.

Built with Next.js, TypeScript, and MongoDB, SwipeStats has achieved profitability, attracted enterprise interest, and built a thriving community on Reddit. The platform handles sensitive data with privacy-first architecture and delivers insights that help users make better decisions.