Revix AI scans your repo, generates its own pattern and architecture rules, and reviews every pull request against them. It keeps learning as the repo changes. Each comment names its rule and is labeled by intent and severity. Free for public repos.
Hey Product Hunt 👋 I'm Uri. Oscar and I are building Revix AI from Barcelona.
Why we built it: LLMs made us write code much faster, but we watched quality drop and incidents go up. Review is where that should get caught, and it usually doesn't, because most review comments don't know how your repo actually does things. So people stop reading them.
Revix starts by scanning your repo and generating its own pattern and architecture rules. You don't write a rulebook. It reviews every pull request against those rules and keeps learning as the repo changes.
Each comment names the rule behind it and is labeled by intent and severity, so you know why it's there and what to fix first. The number we care about is how many comments you act on, not how many we leave.
It works with GitHub, GitLab and Bitbucket Cloud. It's free for public repos, with a 14 day trial and no card for private ones.
It's early and some comments will miss. Please be blunt: run it on a repo you know well and tell us which comment was useless and why. Oscar and I are here all day.
review that learns the repo's own rules is usefull, most tools are so generic 👏 how fast does it pick them up?
where does it learn the rules from? if it’s past review comments, wouldn’t it pick up the ones that were wrong too?
Naming the rule behind each comment is the detail that matters most to me — a review comment without the 'why' is easy to ignore. How do learned rules get retired when the codebase moves on? I'd worry about an old pattern sticking around as a rule long after the team stopped following it, and having to argue with the reviewer about it in every PR.
Last year Claude Code went through a few weeks of ignoring CLAUDE.md, so a rule being written down doesn't mean it gets followed. Checking every PR against the repo's own rules, and naming the rule in each comment, is a much better place to catch it.
Hello there,
I'm Oscar, the other co-founder.
I wanted to explain quickly the story behind Revix AI:
Uri and I found that in this AI era we were reviewing more than coding in our team, and that mostly ended up with us not being able to carefully check everything in a PR, just a quick look at each one. Of course we then tried other AI code reviewers out there, but we could not trust any of them. They just added so much noise that other devs stopped reading the bot comments. We needed a 1 to 1 replacement for us, an AI senior reviewer that matches our style and let us focus on the more human things about coding.
Once we achieved that internally, we thought this was too good not to share with everyone, and that is why we put tons of hours into the afternoons and weekends to make it even better, till it became our main project. Today we are announcing it to the world, and we cannot be more proud of what we've made.
Hope you guys like it as much as we do!
About Revix AI on Product Hunt
“AI code review that learns your repo's own rules”
Revix AI launched on Product Hunt on October 27th, 2026 and earned 110 upvotes and 10 comments, placing #13 on the daily leaderboard. Revix AI scans your repo, generates its own pattern and architecture rules, and reviews every pull request against them. It keeps learning as the repo changes. Each comment names its rule and is labeled by intent and severity. Free for public repos.
Revix AI was featured in Software Engineering (43.3k followers), Developer Tools (522.4k followers) and Artificial Intelligence (482.8k followers) on Product Hunt. Together, these topics include over 234.9k products, making this a competitive space to launch in.
Who hunted Revix AI?
Revix AI was hunted by Oriol Viladrosa. A “hunter” on Product Hunt is the community member who submits a product to the platform — uploading the images, the link, and tagging the makers behind it. Hunters typically write the first comment explaining why a product is worth attention, and their followers are notified the moment they post. Around 79% of featured launches on Product Hunt are self-hunted by their makers, but a well-known hunter still acts as a signal of quality to the rest of the community. See the full all-time top hunters leaderboard to discover who is shaping the Product Hunt ecosystem.
Want to see how Revix AI stacked up against nearby launches in real time? Check out the live launch dashboard for upvote speed charts, proximity comparisons, and more analytics.
Oriol Viladrosa
Hey Product Hunt 👋
I'm Uri. Oscar and I are building Revix AI from Barcelona.
Why we built it: LLMs made us write code much faster, but we watched quality drop and incidents go up. Review is where that should get caught, and it usually doesn't, because most review comments don't know how your repo actually does things. So people stop reading them.
Revix starts by scanning your repo and generating its own pattern and architecture rules. You don't write a rulebook. It reviews every pull request against those rules and keeps learning as the repo changes.
Each comment names the rule behind it and is labeled by intent and severity, so you know why it's there and what to fix first. The number we care about is how many comments you act on, not how many we leave.
It works with GitHub, GitLab and Bitbucket Cloud. It's free for public repos, with a 14 day trial and no card for private ones.
It's early and some comments will miss. Please be blunt: run it on a repo you know well and tell us which comment was useless and why. Oscar and I are here all day.