Intel® Collaboration Suite for WebRTC (Intel® CS for WebRTC)

Create high-performance, reliable, and scalable real-time communication solutions.

  • Server and client tools to deliver RTC experiences with video conferencing capabilities
  • Optimized for Intel® architecture to take full advantage of Intel® hardware acceleration for video encode and decode
  • Integrated real-time video analytics capability powered by the Intel® Distribution of OpenVINO™ toolkit

SDK Capabilities

Client SDK

Intel® CS for WebRTC provides four separate client SDKs to allow development of real-time communication applications:

  • Android* applications using the Intel CS for WebRTC Client SDK for Android
  • Web applications using the Intel CS for WebRTC Client SDK for JavaScript*
  • iOS* applications using the Intel CS for WebRTC Client SDK for iOS
  • Windows* applications using the Intel CS for WebRTC Client SDK for Windows

Main features include:

  • Peer-to-peer (P2P) and conference communications
  • High-performance video codecs by leveraging from the device hardware acceleration for VP8, VP9, H264, and HEVC
  • G.711, G.722, iSAC, Opus, and pluggable AAC for audio codec
  • Mainstream browsers support includes Chrome*, Firefox*, Safari* and Microsoft Edge*
  • Fine-grained API control on codec type, resolution, frame rate, and bitrate configurations
  • High reliability with auto error recovery and comprehensive error handling
  • Greater flexibility through customized stream input APIs with raw and encoded video frames as well as image filtering channel for mobile native SDKs
  • Strong adaptability through optimized QoS control to media processing and transmission based on WebRTC technology
  • Excellent client connectivity through NAT and firewall traversal with STUN, TURN, and ICE support
  • Close monitoring through real-time network statistics report for all connections

Conference Server

This server provides an efficient WebRTC-based video conference service that scales a single WebRTC stream out to many endpoints.

  • Flexible and Adaptive MCU & SFU Server
    The MCU server allows participants with different processing capabilities and network bandwidths to use video conference rooms that provide forward and mix streams. It supports the VP8, VP9, H.264, and HEVC video codecs, and G.711, G.722, iSAC, Opus, and pluggable AAC audio codecs. Developers can customize the mixed video layout, compliant with RFC5707 (MSML).
  • High-Performance Media Processing Capability
    The MCU server is built on top of Intel® Media Server Studio. It is highly optimized for Intel® Core™ and Intel® Xeon® processors with Iris® Pro and Intel® HD Graphics technology. Thus, the server can deliver cutting-edge streaming media performance with high cost-effectiveness. For more information about Intel Iris Pro technology, visit
  • Easy to Deploy, Integrate, and Scale
    This server can be deployed with limited steps, and provides pluggable integration modules as well as open APIs to work with existing enterprise systems. Additionally, it can be easily scaled to cluster mode and serve many more users.
  • High Availability with Fault Tolerance or Resilience
    These server components provide fault tolerance or resilience to help achieve RTC service’s high availability. According to different component characteristics, either auto error recovery or error report back plus resource cleanup service are provided.
  • Secure and Reliable with Intelligent QoS support
    The server ensures conference data security through HTTPS, secure WebSocket, SRTP-DTLS, etc. It provides Intelligent QoS control (such as FIR, NACK, FEC), dynamic bit-rate control, and protects the conference quality against high packet loss and network bandwidth variance.

Media Analytics Server

This server enables media analytics for streams from an MCU. It features:

  • The ability to pull video streams from an MCU for analytics and push video streams to an MCU for republishing
  • Hardware-accelerated video decoding and encoding, and video preprocessing and post-processing
  • A series of use cases for prebuilt real-time video analytics plugins, including face detection, face recognition, body recognition, and smart classrooms
  • A distributed analytics engine that supports large-scale deployment on the cloud
  • A RESTful analytics API interface for easy programming
  • A plugin API interface for implementing customer-defined video analytics use cases that's highly optimized for Intel® platforms, including:
    • CPU
    • CPU with integrated graphics (iGPU)
    • FPGA
    • VPU (through the Intel® Distribution of OpenVINO™ toolkit)