frAIgrant is a content-based recommendation system for perfumes. We analyze ingredients and the notes of each fragrance and weigh them according to the importance of the notes. You'll get recommend the most fitting fragrance, based on your taste.
Search for the most fitting fragrance for your taste
frAIgrant is a content-based recommendation system for perfumes. We analyze ingredients and the notes of each fragrance and weigh them according to the importance of the notes. You'll get recommend the most fitting fragrance, based on your taste.
Hello, Product Hunt community!👋 We are thrilled to launch our first product here📌 The idea for frAIgrant came to me when I was doing an internship and had no way to try new perfumes when I wanted to try something new. So my co-founder Johannes and I decided to build a platform that lets you search for a new perfume if you already know in which direction it should go➡️ Especially in today's day and age you don't have a lot of opportunities to find a new perfume that exactly matches your taste. Al
Interesting product! I am so curious about who your biggest customers will be! :)
Congrats on your launch! I was actually looking for a new cologne too! Great product!!!
Congrats on the launch. Some sensible suggestions came out - I'm still sad that there's nothing similar to Vert D'encens from TF and they discontinued it! I'd love to see this extended to recommendations - people who liked X also liked Y, but using your similarity score to help improve that recommendations model. Using the similarity should allow for collecting niche fragrances into similar segments so it's not just popular scents that get promoted. I like quite a range of scents, but wonder if
The scores reflect launch-period engagement. Historical data is preserved and doesn't change retroactively. The build date at the bottom shows when the index was last refreshed.
Check the similar products section on this page, or browse the category pages linked in the tags above. Each category page shows all products for a given year, sorted by engagement.
A measure of community engagement at launch. Higher means more people noticed and interacted with the product. It's a traction signal, not a quality rating.
Discussion threads divided by interest score. Above 0.30 is strong. Below 0.15 suggests the product got clicks but not conversation.