Orchestrating Real-Time Multimodal Pipelines & Vision Latency in Uvilox AI

Hi builders! At Uvilox AI, we are building low-latency, real-time pipelines that process hand-landmark computer vision models alongside Speech-to-Text (STT) and Text-to-Speech (TTS) streams.

Our Current Challenge & Tech Stack:

• Stack: OpenCV, MediaPipe, TensorFlow/Keras, LiveKit, WebRTC, FastAPI.
• Goal: Keeping frame extraction, landmark classification, and audio generation under 300ms to maintain natural conversation flow.

I’d love to discuss:

• Best practices for optimizing multi-modal streaming latency in production.
• Strategies for running lightweight vision classification models at the edge vs. server-side GPU orchestration.
• Handling frame drops and asynchronous media buffers in real-time WebRTC streams.