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🌌 Nextro Media

Enterprise-Grade P2P & SFU Video Conferencing Engine

Nextro Media is a high-performance, developer-first video networking platform. It features a unique Hybrid Signaling Engine that seamlessly transitions between ultra-low latency Mesh (P2P) for small groups and a powerful Go-based SFU for large-scale enterprise meetings.


🚀 Vision: Scaling to 20+ Participants

Nextro is engineered for growth. While many platforms struggle with bandwidth at scale, Nextro uses a custom Selective Forwarding Unit (SFU) built in Go to orchestrate massive meetings without crushing the client's internet connection.

Important

V2.0 Optimization Status: We are currently implementing Active Speaker Switching. This allows the engine to intelligently prioritize the high-definition video of the current speaker while sending low-bandwidth thumbnails for other participants, saving up to 80% bandwidth in large rooms.


🛠 Tech Stack

  • Backend: Go (Pion WebRTC) — High-concurrency media orchestration.
  • Frontend: React (SDK) — Modern, glassmorphic UI components.
  • Packaging: Docker — Enterprise-ready deployment containers.
  • Signaling: Custom WebSocket protocol with Hybrid Mesh/SFU fallback.

📦 Getting Started

1. Backend Packaging (Docker)

The engine is pre-packaged for instant deployment.

cd engine
docker build -t nextro-engine .
docker run -p 8080:8080 -p 50000-50100:50000-50100/udp nextro-engine

2. Frontend SDK

Nextro provides a professional React SDK to build your UI in minutes.

npm install @nextroford/media-react

🔒 Security: HMAC Shield

Nextro includes a built-in Security Shield (HMAC signature validation) to prevent "Zoom-bombing" and unauthorized room access. Every signaling message is verified against a secure secret key.


⚖ License

Distributed under the MIT License. See LICENSE for more information.


👨‍💻 Author

Jherson Aguto - Principal Architect

About

A high-performance, enterprise-grade video conferencing engine featuring a custom Go-based SFU, React SDK, and hybrid signaling for seamless Mesh-to-SFU scaling (Optimized for 20+ participants).

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