Advanced AI Vision Search and Reasoning with the VAST InsightEngine with NVIDIA? AI Blueprints

AI is redefining the way organizations process, search, and reason over vast amounts of video data. The ability to extract meaningful insights from video in real time is no longer a futuristic concept—it is happening today, thanks to advancements in high-performance AI inference, large-scale video search, and multimodal reasoning.

The combination of VAST InsightEngine and NVIDIA NIM(?) Microservices?transforms raw video streams into actionable intelligence at an unprecedented scale.

The Opportunity

The constant evolution of AI promises to transform how organizations harness video data into value through agentic AI pipelines—unlocking real-time analysis, insight generation, and content creation at unprecedented scale.

We now have endless possibilities to build autonomous workflows that analyze long forms of video content, extract rich contextual insights, dynamically generate personalized content and search vast archives of data.

The disruption will impact a variety of industries such as media and entertainment, security, robotics, and autonomous systems, and many more.

This opens the door to incredible user experiences—from interactive video assistants to real-time content recommendations that boost engagement and brand impact. The richness of the video modality can enhance AI reasoning and insight, enabling more accurate, high-fidelity decision-making. And because these insights are generated as events unfold, they are not only relevant but also interactive—empowering businesses to react instantly, personalize experiences at scale, and drive transformative outcomes across industries.

The Challenge

Managing, storing, and processing massive volumes of unstructured video data poses a significant challenge for most data-intensive organizations. This stems from legacy systems posing a constant tradeoff between storing large-scale video datasets and delivering real-time performance at an affordable cost. As video data fuels insights, which in turn generates more data, this data flywheel accelerates, placing even greater strain on the infrastructure.

The problem is rooted in the traditional data stack, where storage and database architectures, as well as CPU-centric compute environments struggle to keep pace with the explosive growth of video streams. These outdated systems force practitioners to stitch together disparate solutions—ranging from storage and databases to compute and orchestration—just to enable agentic workflows. This patchwork approach creates operational complexities, introduces data and compute silos, and leads to inefficiencies across the entire AI pipeline.

That Changes Today: Enter the VAST InsightEngine + NVIDIA Inference Microservices

The VAST InsightEngine is a core capability of the VAST Data Platform, revolutionizing how organizations process and analyze video data. The VAST InsightEngine benefits from a unified system that seamlessly integrates an unstructured datastore, a structured database, serverless compute infrastructure, and an AI pipeline orchestration framework. This holistic approach enables organizations to host and execute end-to-end AI agentic workflows natively, unlocking unprecedented efficiency and intelligence in video data processing.

Built on the the VAST Data Platform’s disaggregated, shared-everything (DASE) architecture, the VAST InsightEngine leverages the platform’s unified data foundation to deliver real-time, scalable AI-powered insights.

The VAST InsightEngine's ingest and retrieval technology is accelerated by NVIDIA GPU compute as well as NVIDIA NIM Microservices, allowing best-in-class reasoning and vision AI capabilities. With NVIDIA NIM at its core, InsightEngine simplifies complex agentic workflows, enabling businesses to transform raw video streams into actionable intelligence in real-time.

VAST InsightEngine: A New Paradigm for Vision AI

VAST InsightEngine combined with NVIDIA AI Blueprint for Video Search and Summarization (VSS) addresses these challenges by providing an integrated platform that simplifies and accelerates Vision AI workflows. This powerful combination enables organizations to:

• Seamlessly Ingest and Process Video Data: High-performance data ingestion through interfaces such as object-storage (S3), filesystems (NFS/SMB), event streaming like Kafka and Python SDKs allows real-time capture of imagery and video.
• Run Autonomous AI Pipelines: Trigger AI models and functions upon data ingestion, enabling real-time analysis, semantic indexing and dynamic insight generation.
• Deploy Vision Models Effortlessly: A catalog of optimized NIMs for tasks like object detection, OCR (optical character recognition), scene summary, visual data generation and multimodal AI workflows.
• Break Down Data Silos: Unify structured and unstructured data across storage, databases, and compute, ensuring a seamless flow from ingestion to insight.
• Maintain Enterprise-Grade Security and Governance: With row-level access control including derived data and vectors, atomic updates, and multi-tenant governance, organizations can maintain compliance and control.

With NVIDIA AI Blueprint for VSS, AI-powered vision intelligence is not just possible—it’s seamless. By leveraging the VAST Data Platform and VAST InsightEngine, we remove the barriers of scale, complexity, and infrastructure silos.

Real-World Application: NHL Video Intelligence

The National Hockey League (NHL) manages hundreds of thousands of hours of game footage and tens of petabytes of sensor data, all stored on the VAST Data Platform. Sifting through this dataset in real time was previously an insurmountable task. With VAST InsightEngine, the NHL now has the potential for:

• ?Instant Video Retrieval – sub-second searching across petabytes of hockey footage, revolutionizing production workflows.
• Automated Content Personalization – AI-driven agentic workflows dynamically ingest, classify, clip, tag, and assemble customized video experiences at scale and take permitted actions.
• Real-Time AI Reasoning – tailored AI agents process live game feeds for customized uses such as automated statistical and strategy insights, fantasy recommendations, and intelligent media distribution.

Automated Content Generation: Agentic Workflows

AI agents have the potential to play a pivotal role in automating the ingestion, processing, and distribution of NHL video content:

1. Smart Ingestion Agents – Automatically detect key game moments, extracting relevant video feeds and metadata.
2. Context-Aware Clipping – AI tags significant plays, player movements, and crowd reactions, enabling seamless highlight creation to help NHL Producers magnify and accelerate their content creation efforts.
3. Dynamic Content Assembly – Personalized montages, analysis clips, and recaps curated based on fan engagement patterns.
4. Event-Triggered AI Processing – Real-time events like goals and assists that trigger AI pipelines to generate ready-to-publish media.

What’s Next: AI-Powered Fan Experiences

AI is still in its early days of reshaping sports engagement, and we’re only scratching the surface of how it can power future fan experiences. One can imagine a future where AI not only personalizes content but also enhances real-time storytelling, predicts game outcomes, and even creates hyper-interactive ways for fans to participate in the action. While some of these capabilities are emerging today, the full potential of AI in sports is still unfolding—setting the stage for an entirely new era of fan engagement. Here are some examples of future fan experiences:

• Fantasy-Focused Fan – Imagine an AI-driven experience that seamlessly compiles a personalized, multi-game stream by pulling iso-cam views from every arena. The system intelligently alerts users when a player from their fantasy team takes the ice, allowing instant toggling between feeds for a real-time, customized viewing experience.
• International Fan – With real-time search and AI-powered translation, fans can experience the game in their preferred language. A Swedish fan, for example, could query a specific play in their native tongue and immediately switch to a Swedish-language broadcast featuring localized analysis.
• Avid Fan Analytics – AI overlays real-time game data—like player movements, puck tracking insights, and probability-based predictions—providing a deeper, more immersive viewing experience. During power plays or critical game moments, AI enhances understanding with instant, on-screen analytics.
• Social Media Highlights – AI agents detect key game events— game-winning goals, or electric celebrations—automatically clipping and distributing highlights across social media, ensuring fans never miss a moment.
• Deep Archive Retrieval – AI-powered visual search allows fans to pull historical footage in ways never before possible. Imagine instantly finding clips of Stanley Cup-winning players from a specific country, seamlessly linking past and present to enhance today’s narratives.

These innovations represent just a glimpse into what’s possible. Imagine the endless possibilities of unlocking hundreds of thousands of hours of NHL footage. and explore what’s possible.

Transform AI Video Workflows

With VAST and NVIDIA, organizations can unlock the full potential of video intelligence at an unprecedented scale. By eliminating infrastructure complexity and harnessing the power of AI-driven search and reasoning, businesses can drive real-time insights, personalized experiences, and operational efficiency.

Ready to transform your video AI workflows? See the VAST InsightEngine and NVIDIA NIM in action at NVIDIA GTC 2025 in VAST booth #733. And join the conversation on Cosmos!