This product was not featured by Product Hunt yet. It will not be visible on their landing page and won't be ranked (cannot win product of the day regardless of upvotes).
Argus
Open-source AI code review that learns from your team
Argus reviews GitHub pull requests with specialist agents for bugs, security, architecture, and regressions. It adjusts review depth to each change and asks every finding to explain a concrete failure and a fix. Team feedback and past fixes become memory for future reviews. See which checks ran and what each review cost. Open source under AGPL-3.0, self-hostable, and bring your own LLM key.
Hi Product Hunt! I built Argus to make code reviews useful across more than one pull request. A team's past fixes and review feedback should help catch the next bug.
Argus adjusts review depth to the change, uses specialist reviewers, and asks findings to include a concrete failure scenario and a fix. It learns from reactions and replies, and shows the checks and token costs behind each review.
You can self-host it and bring your own LLM key. The code is open source under AGPL-3.0.
A special thank you to the qBraid team!
I wrote a walkthrough of how Argus's memory works, including the diagrams and dashboard images in this gallery: https://x.com/belazyAF/status/21...
I'd love to hear what your current reviewer keeps getting wrong, and what you wish it remembered about your codebase.
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About Argus on Product Hunt
“Open-source AI code review that learns from your team”
Argus was submitted on Product Hunt and earned 2 upvotes and 1 comments, placing #150 on the daily leaderboard. Argus reviews GitHub pull requests with specialist agents for bugs, security, architecture, and regressions. It adjusts review depth to each change and asks every finding to explain a concrete failure and a fix. Team feedback and past fixes become memory for future reviews. See which checks ran and what each review cost. Open source under AGPL-3.0, self-hostable, and bring your own LLM key.
Argus was featured in Developer Tools (519.9k followers), Artificial Intelligence (479.2k followers) and GitHub (41.4k followers) on Product Hunt. Together, these topics include over 237.2k products, making this a competitive space to launch in.
Who hunted Argus?
Argus was hunted by Dhruv Khara. 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 Argus stacked up against nearby launches in real time? Check out the live launch dashboard for upvote speed charts, proximity comparisons, and more analytics.
Dhruv Khara