Hey Product Hunt! 👋 I'm Shikhar, creator of gg-friggin-ez

Why I built this
Back when I worked in the real-money gaming industry, chat moderation was one of those problems that never had a good answer - too slow, expensive, or dumb to catch anything past a static keyword list. I've since moved into backend/AI engineering, and gg-friggin-ez is what happens when that old problem meets the current stack: System 1 models like Jev and Laya that enable real-time, multilingual toxicity screening cheap enough to run on every single message.

Pre-LLMs: Fast, but brittle - traditional filters and ML/NLP models struggled with Romanized Indic, slang, ASCII art, and creative evasion.
LLMs: Smart, but too expensive to run at scale.
System 1 Models (Jev, Laya): Single forward-pass decision engines built for real-time classification - sub-500ms end-to-end, deterministic output, and pennies per million tokens.

So I built gg-friggin-ez around it.

What it does
• Evasion-proof: Catches Romanized Indic profanity, leetspeak & ASCII-art evasion
• Deterministic actions: Converts toxicity into ALLOW, REVIEW, CENSOR, BAN
• Rich telemetry: Returns confidence scores, evasion detection flags, and primary language classification.
• Lightning-fast: sub-500ms moderation
• Ultra-low cost: ~$0.000042/msg using Jev ($0.042 per million tokens), or $0 inference cost using self-hosted open-source models

Pluggable Architecture & Bring Your Own Model (BYOM)

While gg-friggin-ez ships with TypeSafe AI's Jev as the default out-of-the-box engine, it is completely decoupled, so you can point it to your own System 1 models.

It's 100% free and open-source.

• npm i gg-friggin-ez
• GitHub: https://github.com/ItisShikhar/g...
• Demo: https://itisshikhar.github.io/gg...

Ever seen someone outsmart a chat filter? Tell me how. Let’s see if gg-friggin-ez catches it.

gg-friggin-ez

Fast & free profanity and toxicity screening via Jev & Laya

Fast & free profanity and toxicity screening via Jev & Laya