Bypassing full-frame rendering to hit sub-80ms AI translation (Uvilox AI)

Hey IH,

I'm the founder of Uvilox AI (https://uvilox-aiwebsite.pages.dev/). We are building an AI-powered automated calling system and real-time sign language interpreter to eliminate communication barriers for the deaf community.

The Technical Milestone: > Traditional computer vision models struggle with real-time video translation because heavy, full-frame pixel rendering causes a "brain lag" (high latency). For emergency 911 scenarios, delays are unacceptable. We engineered a proprietary, modular pipeline that processes body language vector spaces, facial landmarks, and hand coordinates concurrently. This allows us to maintain a 97.4% accuracy rate on 200+ ASL/BSL signs while dropping system latency to under 80ms.

Where we are at: > The core technical architecture is validated, and our web presence is live. We are looking to connect with strategic advisors, deep-tech founders, and individuals plugged into the accessibility or impact-investing ecosystem as we prepare to scale our compliance layers.

If you are interested in the intersection of vision AI, healthcare infrastructure, and high-impact tech, let's connect!