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Judgie-AI
Multi-persona AI panel for code reviews & event evaluation
Judgie-AI is an open-source AI evaluation platform. Instead of a single score, it uses 5 expert AI personas (Entrepreneur, Engineer, UX Designer, PM, VC) to review projects from multiple angles. Features: - Multi-persona panel: Balanced & diverse reviews - Mid-event coaching: Tracks team growth with charts - "Objection!" feature: Re-deliberation loop - Admin AI chat: Q&A using source code - Bilingual & Custom Templates Deployable to Railway in minutes.
I’m Yosuke Suzuki, Engineering Manager at Money Forward.
The Problem: It all started when I was asked to judge an international internal hackathon. As a non-native English speaker, I dreaded the pressure of evaluating complex code, watching pitch videos, and writing meaningful, detailed feedback—all under a tight deadline and completely in English. I was terrified that my language barrier would compromise the quality of the judging.
The Solution: I decided to hack the judging process itself and built Judgie-AI. I realized that looking at a project through a single lens isn't enough. So, I built a panel of 5 distinct AI personas—a serial entrepreneur, principal engineer, UX designer, senior PM, and a VC investor. They don't just score; they generate multi-angle, bilingual feedback.
At the actual event, participant satisfaction averaged 4.62/5, and organizers rated it 4.67/5 for reducing judging burden. More importantly, it evolved from a mere "scoring machine" into a growth accelerator, helping teams iteratively improve their ideas during mid-event招consultations.
Going Global & Beyond Hackathons: Realizing this was a universal challenge, I resolved the initial session management issues, rebuilt the UI, and released it as a robust OSS platform. Plus, it’s no longer just for hackathons—via JSON templates and GitHub Gist integration, you can easily load custom personas for startup pitches, hiring, or architecture reviews.
You can deploy it to Railway in just a few minutes. I would love to hear your thoughts, feedback, and what kind of evaluation templates you would build with it!
Let's change how we evaluate and accelerate project growth together! 🚀⚖️
About Judgie-AI on Product Hunt
“Multi-persona AI panel for code reviews & event evaluation”
Judgie-AI was submitted on Product Hunt and earned 5 upvotes and 7 comments, placing #99 on the daily leaderboard. Judgie-AI is an open-source AI evaluation platform. Instead of a single score, it uses 5 expert AI personas (Entrepreneur, Engineer, UX Designer, PM, VC) to review projects from multiple angles. Features: - Multi-persona panel: Balanced & diverse reviews - Mid-event coaching: Tracks team growth with charts - "Objection!" feature: Re-deliberation loop - Admin AI chat: Q&A using source code - Bilingual & Custom Templates Deployable to Railway in minutes.
On the analytics side, Judgie-AI competes within Open Source, Developer Tools, Artificial Intelligence and GitHub — topics that collectively have 1.1M followers on Product Hunt. The dashboard above tracks how Judgie-AI performed against the three products that launched closest to it on the same day.
Who hunted Judgie-AI?
Judgie-AI was hunted by Suzuki Yosuke. 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 Judgie-AI including community comment highlights and product details, visit the product overview.
Suzuki Yosuke
Hi Product Hunt community! 👋
I’m Yosuke Suzuki, Engineering Manager at Money Forward.
The Problem:
It all started when I was asked to judge an international internal hackathon. As a non-native English speaker, I dreaded the pressure of evaluating complex code, watching pitch videos, and writing meaningful, detailed feedback—all under a tight deadline and completely in English. I was terrified that my language barrier would compromise the quality of the judging.
The Solution:
I decided to hack the judging process itself and built Judgie-AI.
I realized that looking at a project through a single lens isn't enough. So, I built a panel of 5 distinct AI personas—a serial entrepreneur, principal engineer, UX designer, senior PM, and a VC investor. They don't just score; they generate multi-angle, bilingual feedback.
At the actual event, participant satisfaction averaged 4.62/5, and organizers rated it 4.67/5 for reducing judging burden. More importantly, it evolved from a mere "scoring machine" into a growth accelerator, helping teams iteratively improve their ideas during mid-event招consultations.
Going Global & Beyond Hackathons:
Realizing this was a universal challenge, I resolved the initial session management issues, rebuilt the UI, and released it as a robust OSS platform. Plus, it’s no longer just for hackathons—via JSON templates and GitHub Gist integration, you can easily load custom personas for startup pitches, hiring, or architecture reviews.
You can deploy it to Railway in just a few minutes. I would love to hear your thoughts, feedback, and what kind of evaluation templates you would build with it!
Let's change how we evaluate and accelerate project growth together! 🚀⚖️