In episode 2 of the Video at Work Podcast, Vbrick CEO Paul Sparta sits down with Aragon Research Lead Analyst Jim Lundy for a deep and timely conversation about the growing expectations customers and employees have for video—and how this accelerating demand has left many enterprises scrambling to keep up.
The enterprise video landscape is undergoing a dramatic and sustained transformation. Organizations are facing what Paul describes as a “video tsunami,” an unstoppable surge in the creation, storage, and use of video content across every function of the business. In the episode, Paul reflects on Vbrick’s evolution from its early days providing hardware encoders to its position today as a fully cloud-native SaaS platform. This progression mirrors the industry’s shift: video is no longer a supplementary medium but a critical knowledge asset that fuels daily operations.
The use cases extend well beyond executive town halls and conferencing. Video now supports just-in-time training and microlearning, enabling employees to get the information they need exactly when they need it. It powers IT support and troubleshooting workflows, offering faster, more intuitive guidance than static documentation. Field service teams rely on video to document onsite work, validate maintenance procedures, and improve safety compliance. In industries with distributed operations, such as logistics and transportation, video assists with fleet management and supply chain optimization, helping organizations monitor conditions, ensure accountability, and streamline processes.
Meanwhile, the rise of computer vision is reshaping how enterprises analyze real-world environments. Dash cams, body cams, and security systems are continuously generating massive volumes of visual data. Yet despite the value in these recordings, many organizations still struggle to index, search, and act on what these videos contain. Making sense of this content at scale has become one of the most pressing challenges in enterprise technology.
This is where AI becomes transformative. AI-driven video analysis is turning raw video into structured, actionable data. Vbrick’s platform brings advanced capabilities—including automatic indexing, multi-language transcription, and real-time dubbing—that dramatically reduce the friction involved in managing large video libraries. As AI systems grow more interconnected, the Model Context Protocol (MCP) is emerging as a foundational standard for interoperability. Vbrick is embracing MCP to let organizations use their video libraries as a live, governed data layer for agentic workflows within systems such as Microsoft Copilot, Claude, OpenAI, Salesforce Agentforce, and ServiceNow’s Now Assist. With this integration, AI agents can securely interact with video content to retrieve knowledge, support decision-making, and orchestrate tasks across business applications—all without exposing sensitive data.
With the rapid rise of AI comes equally rapid concern about authenticity. Organizations must navigate a world where AI-generated video is increasingly sophisticated. Vbrick is leading an industry shift from traditional deepfake detection to source verification through its new Verified Authentic framework. Instead of attempting to detect fakes after the fact, the framework ensures content is traced, validated, and trusted from the moment it is created.
Looking ahead, the conversation highlights the next frontier: large image models and advanced ingestion management systems that can handle the explosive growth of enterprise video as hybrid work becomes the norm. As Paul and Jim discuss, organizations that invest now in scalable, secure, AI-ready video infrastructure will be best positioned to harness video as a strategic asset—not just a communication tool, but a core driver of productivity, insight, and operational excellence.