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Agenario
Prove your AI-built app is ready to launch.
Agenario is the evidence-first launch review platform for AI-built apps. Scan a GitHub repo, ZIP, or live URL for launch blockers across security, access control, payments, compliance, performance, reliability, and UX. Unlike generic AI code review, Agenario links findings to code, impact, confidence, reproduction steps, and runtime proof when available—then helps you fix and rescan before users find the problem.
Hey Product Hunt! I built Agenario after seeing a growing problem with vibe coding: it is easier than ever to build and deploy an app, but much harder to know whether it is actually safe and ready for real users.
A founder can launch a beautiful app in a weekend, while missing issues such as exposed credentials, broken access control, payment-flow mistakes, missing error handling, mobile failures, or compliance gaps.
Agenario is designed to be the review layer before launch. You can submit a GitHub repository, ZIP file, or live URL. It maps the app, checks important launch risks, and turns findings into evidence: affected code, file and line references, impact, confidence, reproduction steps, and fix guidance. For supported flows, it can also run browser-based checks and show runtime proof.
The goal is not to overwhelm founders with vague warnings. It is to answer one question clearly:
“Can I launch this app with confidence?”
I would genuinely love feedback on:
1. Which launch risks worry you most when shipping AI-built apps?
2. Would you prefer a one-time deep launch audit or ongoing monitoring?
3. What evidence would make you trust a tool like this enough to act on its findings?
Thanks for checking it out.
About Agenario on Product Hunt
“Prove your AI-built app is ready to launch.”
Agenario was submitted on Product Hunt and earned 0 upvotes and 1 comments, placing #99 on the daily leaderboard. Agenario is the evidence-first launch review platform for AI-built apps. Scan a GitHub repo, ZIP, or live URL for launch blockers across security, access control, payments, compliance, performance, reliability, and UX. Unlike generic AI code review, Agenario links findings to code, impact, confidence, reproduction steps, and runtime proof when available—then helps you fix and rescan before users find the problem.
On the analytics side, Agenario competes within Developer Tools, Artificial Intelligence and Security — topics that collectively have 991.2k followers on Product Hunt. The dashboard above tracks how Agenario performed against the three products that launched closest to it on the same day.
Who hunted Agenario?
Agenario was hunted by Moganti Pranav Raj. 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.
For a complete overview of Agenario including community comment highlights and product details, visit the product overview.
Moganti Pranav Raj