Alternatives
Products that do what RoofQuant does
Bringing Wall Street insights to US housing market
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Hello Hacker News! My name is Anonyo, and I am a seventeen-year-old from Southeast Michigan. This is wallstreetlocal, my passion project for the last year (and a half). I've posted this before, but I've finally open-sourced this entire project, so I thought I'd post it again. Heres the short pitch. The Securities and Exchange Commission (SEC) keeps record of every company in the United States. Companies whose holdings surpass $100 million though, are required to file a special type of form: the 13F form. This form, filed quarterly, discloses the filer's holdings, providing transparency into…
2024 · github.com
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A framework for deciding when/where/how to buy a home
2020
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- 19WM
Hi HN! At Open Listings, we build technology to make buying a house simpler and more affordable. Ultimately, we want to make buying a house as simple as clicking a button. Our core technology is really our transaction process. While we also provide some shopping tools for house hunters, we recognize that people don’t just use 1 site when they’re searching for a home. In the spirit of supporting our clients even if they’er shopping on other sites, we made a “buy button” that we hope will work anywhere. When you click, it looks for address and MLS# on your current page and fills them in on our…
2015 · chrome.google.com
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Discover news and investment insights ahead of the market
2020
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We're a small team of 3 engineers, and wanted to make a better way to look for for properties online. Traditional portals (esp. outside of US) are just a bit rubbish for doing anything other than basic searching. So we've: - Created a crawler that reads through estate agents websites to find homes for sale - Parses that through a series of LLMs and other models to understand each home in depth (e.g. floor type, location, total sqft) - Parses every photo through an embeddings vector space so that people can search for whatever they want. Check it out: https://jitty.com Currently…
2025
- 22IB
A while back, I built a simple app to track stocks. It pulled market data and generated daily reports based on my risk tolerance. Basically a personal investment assistant. It worked well enough that I kept going. Now, the same framework helps me with real estate: comparing neighborhoods, checking flood risk, weather patterns, school zones, old vs. new builds, etc. It’s a messy, multi-variable decision—which turns out to be a great use case for AI agents. Instead of ChatGPT or Grok 4, I use mcp-agent, which lets me build a persistent, multi-agent system that pulls live data, remembers my…
2025 · github.com
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Hey HN, I love scrolling through Zillow and spend way too much time thinking a property is gonna be my next home just to find a couple of days of research later what’s the catch. I built this property analyzer to get a quick overview of “the good, the bad, and the ugly” (love spaghetti westerns) for the property. In ~30-45s you get a pretty comprehensive analysis of the history, risks, and everything else about the property, on top of a short AI-generated podcast going over the details. Users can also comment on properties (a feature I always wish I had on Zillow) and guess the final sale…
2025 · trymasterkey.com
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