AI-powered voice agents are transforming communications across industries like telecom, healthcare, and enterprise customer service. But delivering low-latency, natural-sounding AI responses in real time at low costs remains a major challenge. Leveraging the “lightweight AI” of Small Language Models (SLMs) and free open-source stacks can help overcome
WebRTC applications present unique operational challenges that traditional monitoring tools cannot address. Unlike conventional web applications, real-time communication systems operate with complex peer-to-peer connections, dynamic network conditions, and media processing pipelines that can fail silently or degrade gradually. The primary challenge lies in observability. WebRTC applications generate
In a previous post, Reducing Voice Agent Latency with Parallel SLMs and LLMs, we showed how to reduce response times and create more natural conversational experiences using the LiveKit Agents framework. But optimization is only half the equation. Once your voice agents are deployed and handling real
Bringing WebRTC and SIP together is a powerful way to connect modern web applications with traditional phone systems. Whether you’re enabling voice and video in the browser, or linking your app to a PBX and SIP trunk, WebRTC SIP integration allows users to communicate across platforms without
