What an insane ride it's been building this thing.... After coming back from a 2 week trip to Japan to visit my old study abroad friends and professor this past May, I decided to build https://nipponhomes.com then https://nipponhomes.com/analytics . Out of transparency, I'm losing like $2k/year in raw cloud costs (Vercel, Supabase, Zyte, OpenRouter, AWS, etc.) but I am so humbled in how much I've learned just by building this. Tbh, I realize that I am so fortunate to have the time and money to experiment with something like this, as I know many people out there are really struggling with the current market (heck I am getting rejected left and right too by my dream companies). Documenting here some of my learnings to share:
1. I learned how to create a lightweight, custom multi-modal recommendation system; I also ended up getting 2nd place for in Liquid AI's hackathon with this. (https://github.com/angelotc/lfm2-vl-embeddings) . Turns out you just need an MLP or attention layer to fuse two sets of dense embeddings.
3. You need proxies (Zyte, BrightData, OxyLabs, etc.) to scrape at scale if you don't want to build your own proxy rotation system.
4. Wasn't getting sign ups until I added this feature where after a person views 3 listings, they have to sign up. That like 10x'd my signups (#growthhackingiguess)
Ps. I kinda built this out of depression tbh lol as I got rejected to Meta for the 2nd year in a row and Open AI for the 3rd time. The site currently has 8k monthly users, which is super cool, but tbh I don't know if I want to keep working on it anymore as I'm not really learning anymore, and just adding shit here and there. I know the site isn't perfect yet, and I'm getting some interests from major banks, japan real estate consultants ( the folks that help you buy the houses), and competitors (they want the data) in case you folks were interested on who is reaching out.
1. I learned how to create a lightweight, custom multi-modal recommendation system; I also ended up getting 2nd place for in Liquid AI's hackathon with this. (https://github.com/angelotc/lfm2-vl-embeddings) . Turns out you just need an MLP or attention layer to fuse two sets of dense embeddings.
2. Queues + async workers are a must for processing things at scale (listings in my case). Kinda go into it more in this video: https://youtu.be/qXOk7_3vZgQ?si=Mk1l3dYhzdQuvFe3&t=360
3. You need proxies (Zyte, BrightData, OxyLabs, etc.) to scrape at scale if you don't want to build your own proxy rotation system.
4. Wasn't getting sign ups until I added this feature where after a person views 3 listings, they have to sign up. That like 10x'd my signups (#growthhackingiguess)
Ps. I kinda built this out of depression tbh lol as I got rejected to Meta for the 2nd year in a row and Open AI for the 3rd time. The site currently has 8k monthly users, which is super cool, but tbh I don't know if I want to keep working on it anymore as I'm not really learning anymore, and just adding shit here and there. I know the site isn't perfect yet, and I'm getting some interests from major banks, japan real estate consultants ( the folks that help you buy the houses), and competitors (they want the data) in case you folks were interested on who is reaching out.