Virl.ai
The Autonomous Growth Engine for Creators.
29 followers
The Autonomous Growth Engine for Creators.
29 followers
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.
Clip it made during demo: https://youtube.com/shorts/rO-XdVng87Q?feature=share
I’m Ruwail, a CS student and builder from Pakistan. 🇵🇰
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) and slow.
I didn't want to build another wrapper. I wanted to build an autonomous agent that acts as your personal editor.
Under the Hood: A Multi-Stage AI Pipeline Virl.ai isn't just clipping random moments. It's a sophisticated local engine (currently) that we are preparing to scale to the cloud.
Context Engine v2.0: Uses Local Whisper (on-device transcription) to listen to hours of audio. It analyzes a 90-second buffer around loud moments to understand the setup, the joke, and the reaction ensuring clips don't start in the middle of a sentence. Will be cloud computed eventually
👁️ Universal Vision: I trained a custom YOLOv8 model to detect "Facecams," "Game Borders," and UI elements. It dynamically switches layout modes (split screen for gaming vs. full screen for 'Just Chatting') so your clips never look broken.
⚡ Smart Dodge: The editor automatically shifts gameplay footage to avoid 'ghosting' (when your facecam overlays the game), keeping the final vertical video clean and professional.
Why We Are Here & The Future This version runs locally to prove the architecture works. But local processing doesn't scale.
We are opening up 50 spots for our private beta to stress-test the engine.
We are actively seeking Pre-Seed funding to migrate this architecture to a scalable GPU Cloud Infrastructure. This will allow us to:
Process simultaneous streams in real time.
Deploy our "Context Expansion" logic at scale (where the AI autonomously asks for more context if a clip feels incomplete).
Integrate direct auto-posting to TikTok, Shorts, and Reels.
I’d love your feedback
@ruwail_ahmad Does it also work for podcasts or interviews?
@maslamah_muhammad yes sir supports YouTube and twitch
Everyone talks about repurposing content, but nobody has 8 hours to rewatch their own stream If this works as smoothly as it looks, streamers are about to save a lot of time.
@abdullah_azmat it auto mas distributes too
Amazing concept. This automation will save people from alot of trouble.
Does it auto upload as well?
AutonomyAI
That's super impressive. Cant wait to try it :)
@lev_kerzhner although can't afford to shift it on cloud right now I'm trying my best to get it up for early adopters within in 2 weeks :)