Fora Soft Launches Monthly WebRTC & Real-time Video Engineering Report

This monthly report provides direct, hands-on engineering intelligence crucial for streaming industry professionals. The focus on real-world production issues and migration strategies offers immediate value to development teams grappling with complex WebRTC and real-time video deployments. As streaming architectures increasingly depend on stable, low-latency video and voice, such practical field reports can inform technical decisions and mitigate risks. Expect to see similar granular, engineer-driven content emerge as companies seek to differentiate their practical expertise in a crowded market.

Fora Soft's new Ship Log aligns with a broader industry push for transparency and practical insights into real-time communication infrastructure, particularly for AI agents. According to Fora Soft's "2026 LiveKit Multimodal Agents Guide," LiveKit has become the default framework for AI agents due to its architecture, enabling sub-500ms latency and native SIP support. LiveKit Agents 1.5, released in April 2026, is described as the most deployed agent framework on WebRTC, offering adaptive interruption handling and Model Context Protocol (MCP) tool support (per Fora Soft, 2026). The company emphasizes the critical need for low-latency in voice AI, with sub-500ms being the benchmark for natural interaction and 250-400ms being achievable with co-located LiveKit Cloud and model endpoints. Another Fora Soft guide highlights that LiveKit's strength lies in providing the real-time audio and video transport layer, while AI processing, orchestration, and memory reside in external services, promoting flexibility and scalability. This modular approach is essential for addressing compliance for issues like HIPAA, EU AI Act, and PCI-DSS, which require clear boundaries for data handling and security (Fora Soft, 2026). The integration of AI agents as routine participants in WebRTC rooms marks a significant trend, with the agent fleet scaling independently from the Session-Forwarding Unit (SFU) fleet to maintain performance. This is further supported by the industry-wide adoption of cascaded SFU architectures for scaling WebRTC, as detailed in Fora Soft's "WebRTC at Scale" article.