Deploying AI without giving up control
One of the distinguishing characteristics of this framework is its flexibility of implementation.
Unlike cloud-only AI services that require video to be sent to an external platform for processing, VIF supports deployment on-premises, at the network edge, in a private cloud environment, in an air-gapped facility, or in a hybrid architecture.
This approach allows organizations to:
- Maintain full ownership of your video, metadata, and AI output.
- Reduce or eliminate recurring cloud inference and token costs.
- Continue AI processing without an internet connection.
- Leverage your existing server, GPU, and edge infrastructure.
- Deploy new AI models without replacing the underlying platform.
The company says this architecture is particularly attractive to organizations operating under strict security, compliance, and regulatory requirements, such as government agencies, defense organizations, healthcare providers, financial institutions, utilities, and critical infrastructure operators.
NVIDIA partnership adds video authenticity verification
A notable addition to the platform is its native integration with NVIDIA’s Synthetic Video Detector, which allows organizations to determine whether live video was manipulated or generated using artificial intelligence.
With growing concerns about deepfakes and synthetic media, this capability provides a new layer of trust for organizations that rely on live video for investigations, emergency response, and operational decision-making.
The authenticity detection capabilities integrated into Wowza’s video compliance products can be deployed wherever customers choose, including on-premises environments where sensitive video is never under an organization’s control.
Designed for integration
Beyond security operations, VIF is intended to serve as a development platform for system integrators, software developers, and technology partners.
Built on the same APIs, SDKs, and extensibility frameworks already available within Wowza Streaming Engine, this platform enables developers to embed AI-powered video intelligence into custom applications and operational workflows.
Possible integrations include:
- Video Management System (VMS)
- Physical Security Information Management (PSIM) Platform
- Enterprise resource planning (ERP) system
- Customer relationship management (CRM) applications
- IoT platform
- Automated business workflow engine
Rather than locking users into predefined AI capabilities, VIF is model agnostic, allowing organizations to deploy production-ready AI models from Wowza, their own models developed in-house, or third-party products such as NVIDIA’s synthetic video detectors.
Mass production model available at launch
Video Intelligence Framework will be generally available starting July 20, 2026.
Initial production-grade AI models include RF-DETR object detection models and CLIP-based scene analysis, and NVIDIA synthetic video detectors are available to organizations running supported NVIDIA AI infrastructure.
Wowza plans to demonstrate the platform through customer briefings focused on physical security, public safety, transportation, and industrial operations.
Management perspective
“Our vision was that video would become the primary source of data for understanding the world,” said Krish Kumar, CEO of Wowza. “Instead of simply transmitting and storing video, VIF allows organizations to understand it, take action on it, and turn every live stream into a source of real-time operational intelligence.”
Kumar added that the integration of NVIDIA’s synthetic video detector expands the platform with enterprise-scale video reliability and compliance capabilities, while allowing customers to maintain full control over their sensitive data and AI infrastructure.
