WebRTC is a foundational technology behind many real-time communication applications, including telehealth platforms handling sensitive health data and enterprise collaboration tools exchanging confidential business information. While WebRTC offers strong security by design, building a secure application requires more than just relying on its built-in protocols. This WebRTC Security 2025 guide explores WebRTC’s core security mechanisms, such as DTLS and SRTP, alongside the most common implementation risks and best practices. Whether you're developing a browser-based video

Voice AI applications are changing how businesses handle customer interactions and how users navigate digital interfaces. These systems process spoken requests, understand natural language, and respond with generated audio in real time. Building a voice AI application requires understanding speech processing, language models, and real-time communication infrastructure. You need systems that can detect when users finish speaking, convert audio to text, generate appropriate responses, and convert those responses back to audio. This guide covers the

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 the latency and cost barriers of real-time voice AI. At ClueCon 2025, taking place in Chicago from August 4–7, WebRTC.ventures CTO Alberto Gonzalez will give a talk entitled,

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 extensive telemetry data for example, ICE candidate exchanges, DTLS handshakes, media statistics, and network quality metrics, but this data remains largely inaccessible to development teams. When users report

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 conversations, you need comprehensive monitoring to measure latency, track costs, and ensure optimal performance. Voice AI agents present unique observability challenges. Real-time audio processing, variable LLM latency, and

Voice assistants powered by real-time AI are increasingly being used to automate phone-based customer interactions. Whether for contact centers, internal help desks, or voice-driven workflows, a reliable architecture needs to support low-latency audio streaming, accurate speech-to-text (STT), intelligent response generation, and real-time speech synthesis. In this post, we walk through how to build a serverless Voice AI assistant that runs entirely on the scalable power of the AWS infrastructure, using Twilio ConversationRelay as the telephony

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 needing special hardware or downloads. While the goal is clear, the integration process can be complex. WebRTC and SIP use different signaling protocols, media formats, and security models.

Large Language Models (LLMs) have dominated conversations about AI integration in WebRTC, particularly when it comes to voice-based features like transcription, summarization, and intent detection. But there’s an emerging layer that many outside of research circles are missing: Vision Language Models (VLMs). Unlike LLMs, which work with text and speech, VLMs are capable of understanding and generating language based on visual inputs—opening up new possibilities for analyzing what’s happening on camera during a WebRTC session.

Real-time video communication applications face unique scalability challenges that can make or break the user experience. When thousands of users simultaneously join virtual classrooms,  video conferences or other streaming video experiences, traditional autoscaling approaches often fall short. The key to managing predictable traffic spikes in WebRTC applications lies in proactive scaling strategies that anticipate demand before it hits your infrastructure. Scheduling scaling ensures your infrastructure is ready ahead of demand, avoiding the latency issues that

We’re happy to announce that WebRTC.ventures has acquired Peermetrics, the innovative real-time communication analytics platform that has been helping developers monitor and optimize their WebRTC applications since 2021. This strategic acquisition represents WebRTC.ventures’ commitment to supporting open source WebRTC projects while also providing the most comprehensive real-time solutions to our clients. “WebRTC.ventures shares our vision of making WebRTC development more accessible and reliable. Their expertise and resources will allow Peermetrics to reach new heights and

The era of clunky, keypad-driven legacy IVR customer service systems that have long frustrated users is finally over. The future of Interactive Voice Response is truly conversational, and it's ready for prime time. That’s why Deepgram’s State of Voice AI 2025 report says 84% of business leaders are increasing their Voice AI budgets this year. Our expert team at WebRTC.ventures built a Smart IVR Agent that serves as a blueprint for this future: a voice-first

Ensuring optimal Voice AI agent performance is a critical challenge for businesses deploying conversational AI. Poor voice bot interactions can lead to customer frustration, increased support costs, and lost revenue opportunities. From refining bot behavior to perfecting speech recognition and ensuring relevant responses, the journey to continuous improvement of conversational AI demands rigorous testing and keen observability. What if you could automate this crucial testing phase, reducing development costs and preventing voice AI failures from

Since Zoom adopted WebRTC, we've been closely monitoring their developer platform evolution. Zoom's WebRTC-powered Video SDK is a powerful addition to the CPaaS landscape, offering rapid integration, robust performance, and a wide array of features for custom video solutions. At their 2025 Developer Summit, Zoom unveiled significant platform upgrades focused on real-time AI, multimodal streaming, and enhanced customer experience capabilities. Here’s a few from the sessions I was able to attend: RTMS: Real-Time Media Streams

WebRTC.ventures is proud to announce that AVA Intellect, the Live AI Agent platform we've been helping build over the past year, has been acquired by Wowza, a global leader in video streaming infrastructure and technology solutions.  AVA is an AI-native startup specializing in intelligent and embedded agent technology for video platforms. Wowza will be integrating AVA Intellect's agent framework into their platform to deliver video insights and real-time configuration support that adapts to customer needs.

One of the biggest challenges in building real-time AI voice agents is the delay between when a user finishes speaking and when the system responds, known as latency. Even small delays in a Voice AI application can disrupt the natural flow of conversation and harm your user experience. To consistently achieve the kind of sub-second responsiveness necessary for human-like conversational flow without sacrificing answer quality, the webrtc-agent-livekit project takes a holistic approach. It combines the

Adding Voice AI to WebRTC applications presents unique technical challenges and user experience considerations. How do you architect systems that handle real-time audio processing, maintain conversational context, and deliver natural, responsive interactions? And how do you design interfaces that adapt to the dynamic nature of AI-powered communication? In this episode, two members of the WebRTC.ventures team share insights from real-world projects integrating AI agents into live video environments, and designing interfaces for them. Hector Zelaya (WebRTC

WebRTC applications can run into problems on Kubernetes because of the many layers of NAT, which often block UDP and RTP media traffic. STUNner is a WebRTC media gateway built to fix these issues by acting as a reliable STUN and TURN server in Kubernetes environments. In this blog post, we’ll show you how to set up STUNner as a standalone STUN/TURN server on Amazon EKS (Elastic Kubernetes Service), with support for both UDP and

At WebRTC.ventures, we're not just building smart real-time communication applications, we're building them smartly. Instead of asking "How can we use AI?" we started with a better question: “What’s wasting our developers’ time and are there new tools to avoid that?”  The answer led us to integrate AI thoughtfully in our development workflow, but not in the way you might expect. This isn't about replacing developers or chasing the latest AI trends. It’s about people:

Imagine a customer support voicebot that speaks in your founder’s voice, a virtual coach that sounds like you, or an interactive character in a game that talks with a familiar tone. Personalized AI voice assistants built with realistic AI voice generators are transforming how we build more human-centered AI experiences for business, creative, or accessibility-focused applications. In this post, we’ll walk you through how to build a real-time AI voicebot that uses your own cloned

Hector Zelaya, our WebRTC Developer Advocate at WebRTC.ventures, will be a featured speaker once again at the 2025 AWS Community Day México—one of the premier cloud technology events in Latin America. If you’re attending, be sure to look him up! Last year at Community Day, Hector spoke on how generative AI is reshaping contact center customer service, highlighting smarter self-service and personalized experiences powered by AI. He continues to share expertise on automating AI agent