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Streamers spend 8 hours broadcasting and 0 hours distributing. VIRLai fixes this.
It is an AI-native infrastructure that ingests long-form Twitch/YouTube streams, identifies viral moments using Context Intelligence (Audio + LLMs), and autonomously edits them into vertical shorts using Computer Vision (YOLOv8).
Features:
Understands jokes, setups, and reactions (90s buffer).
Detects facecams and game UI to smart-crop instantly.
Runs while you sleep.
Virl.aiThe Autonomous Growth Engine for Creators.
Ruwail Ahmadleft a comment
Clip it made during demo: https://youtube.com/shorts/rO-XdVng87Q?feature=share Iām Ruwail, a CS student and builder from Pakistan. šµš° I built VIRLai because I saw a massive inefficiency in the Creator Economy: Streamers are the hardest working people in content, broadcasting for 8+ hours daily. Yet, 90% of their best footage goes to waste simply because manual editing is expensive ($1000+/mo)...
Virl.aiThe Autonomous Growth Engine for Creators.
Ruwail Ahmadstarted a discussion
Building an autonomous video agent with Gemini 2.0 & YOLOv8, Roast my logic?
I'm a CS student building VIRL-ai ā an autonomous agent that takes 8-hour Twitch streams and turns them into viral TikToks without human help. Most AI clippers just look for "loud noises." I found that approach cuts off the setup to jokes. My Solution: I built a local pipeline (Python) that does two things differently: Context Engine: It grabs a 90-second audio buffer around spikes and uses...