Vbrick Announces Next Wave of AI Advancements, Unlocking Multimodal Intelligence and Agentic Workflows for the Enterprise
Vbrick, the leading end-to-end enterprise video platform (EVP) provider, today announced further expansion of its artificial intelligence (AI) capabilities. This development signals the next phase in its mission to transform video into enterprise intelligence that can power any workflow, tool, or AI system.
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Over the past several years, large language models (LLMs) have transformed how enterprises turn unstructured text and documents into usable intelligence for automation and agentic workflows. The next evolution of AI extends that intelligence beyond text, enabling systems to understand visual and contextual information through large vision models (LVMs), image recognition, and computer vision. Vbrick is uniquely focused on bringing these capabilities together in a single, enterprise-grade platform that allows organizations to interpret video as data, unlocking new value from video at scale.
“Turning video into true enterprise intelligence requires the combined power of LLMs and LVMs along with the critical ability to aggregate video and connect it directly to work processes,” said Paul Sparta, Vbrick chairman and CEO. “Without this foundation, video remains a siloed and underutilized asset rather than a source of strategic intelligence.”
As organizations generate more video than ever before, leveraging its value hinges on the ability to operationalize the information it contains. Vbrick’s latest enhancements advance this vision by enabling enterprises to manage video as an intelligent data layer that is available anytime, anywhere, and to any application or AI agent that requires it.
Advancing Toward Full Video Understanding with Multimodal AI
For much of the last decade, enterprise AI innovation centered on text. As LVMs become more powerful, multimodal AI systems provide the ability to understand and reason across text, images, audio, and video simultaneously, mimicking human ability to combine senses for a deeper understanding.
As the first EVP to introduce multimodal AI through facial recognition, Vbrick is extending years of AI innovation with advanced image, scene, and visual pattern recognition. Vbrick’s enhanced multimodal AI analyzes not only what’s said in a video’s transcript but also what appears on screen, uncovering richer insights from visual, audio, and contextual signals.
When enterprises consolidate video into Vbrick’s platform, multimodal AI can extract greater knowledge, automate more processes, and generate intelligence at scale, including detecting changes in physical environments and interpreting visual cues for sentiment, compliance, and safety monitoring.
Vbrick MCP Server: Video as a Live, Actionable Data Layer
In 2025, Vbrick launched its Model Context Protocol (MCP) server, connecting enterprise video to AI agents and copilots across platforms such as Microsoft Copilot, Claude, OpenAI, ServiceNow Now Assist, and Salesforce Agentforce. In 2026, Vbrick is expanding MCP to deepen these integrations and extend how AI can interact with enterprise video.
With Vbrick MCP server, video becomes an active, queryable data source that AI agents and copilots can use to securely retrieve knowledge, support decisions, and orchestrate tasks across workflows and systems.
“Video data is inherently unstructured, which makes it difficult to organize and use, so critical knowledge often stays hidden,” said Sparta. “By centralizing video storage and interpreting it with AI, we’re turning it into an always-available, enterprise intelligence layer that informs decisions, strengthens processes, and powers modern AI systems.”
Strategic Outlook: Video as an Enterprise-Wide Knowledge Layer
Video captures tacit and contextual knowledge that text alone can’t convey. Vbrick transforms this content into structured intelligence through transcripts, timestamps, semantic context, metadata, and summaries. When this depth of video data is integrated into generative AI workflows, it fundamentally elevates what AI agents can understand and act on.
This intelligence extends beyond recorded content to inward-facing live video streams, such as CCTV and operational monitoring. By interpreting live visual signals in real-time, AI can enable immediate, actionable intervention, shifting from a passive system of record to an active enterprise intelligence layer.
“Instead of sitting idle in storage, video libraries and live streams managed in Vbrick become active knowledge engines that power agentic workflows with a company’s unique knowledge,” said Sparta.
Leading the Future of AI and Video Integration
Vbrick’s multimodal AI and MCP server complement an existing suite of AI capabilities that include contextual smart search, automated metadata generation, transcription, text and audio translation, and an interactive AI video assistant, reinforcing Vbrick’s leadership in enterprise-grade video and AI innovation.
About Vbrick:
Vbrick transforms unstructured video data into a powerful source of enterprise intelligence. As the leading Enterprise Video Platform (EVP) provider, Vbrick’s AI-powered, cloud-native solution delivers the right video asset to any business process or AI agent via MCP (Model Context Protocol). By turning video into a connected data layer that is searchable, secure, and seamlessly integrated, Vbrick enables organizations to harness their content’s full potential and accelerate work at scale. Learn more at vbrick.com.
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