Filadd (YC S21) – Online Courses for LatAm University Admissions

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Hi HN! We are Nico, Agus, Guille, and Joaco and we’re building Filadd — online courses for university admissions exams in Latin America. Not long ago, when we were university students, we built a forum (https://filadd.com) so our college mates could share content, documents, and notes with each other for free. It got a lot of traction, but we couldn’t monetize it. So we looked carefully at our users’ behaviors and noticed a common need: 80% of the students using our forum attended private tutoring classes to prepare for university admissions exams. That is how we decided to build Filadd (https://courses.filadd.com) — a platform that offers online courses for university admissions exams. When we started, we had no money to pay teachers, so we partnered with teachers and shared revenue with them. This model was so good to us that we still maintain it. For each course sale, teachers earn 40% and Filadd earns 60%. This model resulted in the most experienced teachers wanting to work with us and giving excellent service to their students. And it results in 85% of our students reaching their desired score. Now, we work with more than 150 teachers and we are 26 full-time people in the company helping students in Argentina, Chile, Colombia, and Brazil be admitted to the toughest universities. We would love to hear your thoughts and feedback.

Visit product View on Hacker NewsJul 10, 2021

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Hacker NewsMay not resonate with HN audience · Strong signals: ide, io · Missing: https docs, excited, just released

46%46% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

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43%43% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

AppSumoMay struggle as an AppSumo deal · Strong signals: platform, users · Missing: plus, intuitive, reviews

43%43% predicted probability of success on AppSumo, based on ML models trained on real launch data.

Product HuntUnlikely to reach the leaderboard · Strong signals: model, user, using · Missing: mac, agents, macos

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Acquire.comPre-revenue stage for this audience · Strong signals: revenue · Missing: arr, mrr, profit

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BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto

0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

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