Wowza provides a reliable, scalable video streaming platform that simplifies live and on-demand streaming. Their integrated platform and on-premises server software, coupled with builder-focused APIs, enable organizations to quickly develop and deploy video solutions. With over 35,000 implementations across media, enterprise, government, and healthcare, Wowza is a trusted partner known for its SOC 2 compliance and robust infrastructure.
Krish Kumar
CEO
Charlie Good
Co-Founder
David Stubenvoll
Co-Founder & Board Member
Coach Rob-Lover
Chief Executive Officer
Michelle Noon
Board Chairman
Elliot Miller
Head of Operations
Alex Gammelgard
VP of Marketing
Jon Corley
Chief Technology Officer
John Fletcher
VP of Engineering
Bjorn Gustafsson
VP of Engineering Europe
Manish Shah
Director of Engineering, AI
Jay Mele
VP of Global Sales
Tim Dougherty
Director of Sales Engineering
Nick Smith
VP of Channel Sales
Mike Vitale
VP, AI Strategy
Rob Poach
SVP, Head of Customers
Matt Pozek
VP
Wowza has released Streaming Engine 4.11, which introduces support for the Video Intelligence Framework, native ARM64 transcoding, and standardized WebRTC ingest via WHIP and WHEP. The update also addresses security vulnerabilities in several third-party components and improves overall server stability.
Wowza has published a technical guide detailing how to configure its Video Intelligence Framework (VIF) to support various AI models, including object detection, scene analysis, and vision-language models. The framework is designed to run inference independently of the primary live delivery path to ensure stream uptime.
Wowza has published technical guidance for optimizing Wowza Streaming Engine on CPU-only infrastructure to handle high-concurrency WebRTC transcoding. The recommendations focus on decoder implementation, audio codec pairing, memory allocator tuning, and horizontal scaling strategies for camera fleet deployments.
NVIDIA and Wowza have integrated the NVIDIA Synthetic Video Detector into the Wowza Video Intelligence Framework to enable real-time detection of AI-generated content within live streaming workflows. The solution, which uses frequency-domain analysis to maintain accuracy across compressed video, is designed for on-premises, edge, or air-gapped deployment.
Wowza has updated its Video Intelligence Framework (VIF) to allow users to swap AI models, such as RF-DETR and ViFi-CLIP, within existing live streaming pipelines. The update enables custom object detection and scene analysis without requiring changes to ingest or transcoding configurations.
Wowza has introduced its Video Intelligence Framework (VIF), which enables real-time computer vision analysis directly within the Wowza Streaming Engine pipeline. The framework supports multiple output channels, including metadata and webhooks, allowing operators to trigger automated workflows without relying on external post-event analysis.
Wowza has launched the Video Intelligence Framework (VIF), an AI inference layer for the Wowza Streaming Engine that enables custom model integration and synthetic video detection on-premises or at the edge. The framework converts inference results into structured metadata and alerts, supporting delivery via ID3, webhooks, and logs without reliance on metered cloud APIs.
Wowza discusses the architectural considerations for integrating computer vision models into video streaming workflows. The article outlines the importance of decoupling inference from delivery infrastructure to allow for the use of custom-trained, domain-specific AI models.
Wowza explained how traffic management centers can use WebRTC for low-latency operator viewing and tied the guidance to new capabilities in Streaming Engine 4.11, including WHIP/WHEP and configurable STUN/TURN servers.
Wowza published a technical guide outlining best practices for deploying standards-compliant WebRTC architectures, focusing on the distinct roles of SDP/ICE, WHIP/WHEP, and STUN/TURN. The document explains how leveraging HTTP-based signaling protocols like WHIP and WHEP simplifies integration with containerized cloud environments and standard network infrastructure. It also addresses codec considerations, highlighting H.264 as the most compatible option and noting the emerging but uneven support for H.265 and AV1.
