NVIDIA Unveils Agentic AI Blueprints and Models to Revolutionize Enterprise Automation

CES 2025 - how NVIDIA and partners are setting out to simplify agentic AI

NVIDIA took CES as an opportunity to unveil several new families of small, medium, and large foundation models optimized for agentic AI workflows, new blueprints for building AI solutions, and a significant expansion of its agentic ecosystem. In tandem, Accenture has announced twelve new industry agent solutions on top of the NVIDIA platform that support revenue growth management, clinical trial management and industrial asset troubleshooting as part of its AI Refinery for Industry. Accenture has also announced the acquisition of Percipient, a Singapore fintech platform for creating digital twins of banking systems. This tech will be integrated into Accenture's broader agentic AI tooling. At the core of NVIDIA's agentic AI tooling are a new collection of large language models (LLMs), vision language models (VLMs), and retrieval augmented generation (RAG) services optimized for building agentic AI apps. ServiceNow and SAP have announced plans to use NVIDIA's new LLMs purpose-built for agentic AI. Phil Wainewright recently compiled a deep dive into what these mean for SaaS pricing and product. Indeed, all major SaaS vendors are pursuing their own take on the concept. However, Agentic AI is a confusing field with leading enterprise software vendors pursuing different approaches to make it easier to automate or augment various human processes. It's not just about deploying an app but also about orchestrating workflows across multiple apps, components, and APIs. Prebuilt blueprints, launchables and other differently named templates should help enterprises jumpstart this process more quickly. These will make it easier to enforce best practices in configuration management, security, safety, and trustworthiness. NVIDIA has been creating several building blocks for agentic AI, including pre-trained foundation models, a data orchestration framework, an agentic lifecycle management system, and blueprint recipes for building intelligent agents. NVIDIA rolled out several agentic blueprints on its own for synthesizing podcasts from PDF files and searching and summarizing videos. It is also collaborating with vendors specializing in various tooling for AI orchestration that can provide enterprises with various agentic AI options. Anne Hecht, senior director of Agentic AI at NVIDIA says: So this is the first of a set of partners, we're going to be working with to bring new capabilities to managing agentic AI workflows. We're working with this group of partners in particular because they bring traceability and manageability to these autonomous workflows, which, as these go into production and deployment is very important. All of these partners have open source offerings. So, developers can start for free on these open source platforms. And we're really trying to bring agentic AI development skills to the twenty-five million developers out there who are adding agentic workflows and capabilities to their applications. Here is a rundown of the five partners and their blueprints. Accenture has also introduced twelve new agentic AI solutions on top of its AI Refinery framework that helps customize and train domain models, route workloads to various AI tools and models, scan enterprise data into a vector database, and create autonomous knowledge robots. These existing solutions fall under four broad categories: Some see the current agentic AI concept as part of the broader development of a new kind of platform that could be as transformative as mobile and cloud. It began when researchers started finding ways to combine AI systems with retrieval augmented generation (RAG), various enterprise systems, and each other using techniques like prompt chaining and chain-of-thought reasoning. One of the novel aspects of NVIDIA's approach is that it supports tight integration between LLMs that are best suited for processing words, with its Cosmos world foundation models for processing physical world data. The company is taking an expansive view of the concept of physical and virtual agentic AI systems and laying out the plumbing to support it. Rev Lebaredian, Vice-President of Omniverse and Simulation Technology at NVIDIA, says: Now foundation models, distillation, prompting, large context and RAG have paved the way to agentic AI and right around the corner is physical AI. It's only the beginning. Let's talk about where AI is going. The world is about to change dramatically. Soon we'll have billions of physical and virtual robots. NVIDIA creates the platform for companies to build three types of robots: Knowledge robots or agentic AI, generalist robots or humanoid robots, and transportation robots or autonomous vehicles. A lot can go wrong when using some of these new generative AI techniques, including hallucinations, accentuation of biases, and the generation of harmful content. Things get even more complicated when trying to glue multiple tools directly to enterprise processes and allowing them to make decisions autonomously. NVIDIA's recent progress in streamlining the underlying infrastructure will support these kinds of solutions as enterprises work out the kinks. The company has also demonstrated a thoughtful approach in working with leading open source vendors in this arena to help formulate best practices that will lower the bar in building more trustworthy agentic AI systems.

Nvidia launches agentic AI blueprints to automate work for enterprises

Developers can now build and deploy custom AI agents that can reason, plan and take action with Nvidia AI Blueprints that include Nvidia NIM microservices, Nvidia NeMo and agentic AI frameworks from leading providers. New Nvidia AI Blueprints for building agentic AI applications are poised to help enterprises everywhere automate work. Jensen Huang, CEO of Nvidia, made the announcement as part of his CES 2025 opening keynote. With the blueprints, developers can now build and deploy custom AI agents that can reason, plan and take action to quickly analyze large quantities of data, summarize and distill real-time insights from video, PDF and other images. CrewAI, Daily, LangChain, LlamaIndex and Weights & Biases are among leading providers of agentic AI orchestration and management tools that have worked with Nvidia to build blueprints that integrate the Nvidia AI Enterprise software platform, including Nvidia NIM microservices and Nvidia NeMo, with their platforms. These five blueprints -- comprising a new category of partner blueprints for agentic AI -- provide the building blocks for developers to create the next wave of AI applications that will transform every industry. In addition to the partner blueprints, Nvidia is introducing its own new AI Blueprint for PDF to podcast, as well as another to build AI agents for video search and summarization. These are joined by four additional Nvidia Omniverse Blueprints that make it easier for developers to build simulation-ready digital twins for physical AI. Huang said in his keynote that every programmer will need agents to create code to keep up. To help enterprises rapidly take AI agents into production, Accenture is announcing AI Refinery for Industry built with Nvidia AI Enterprise, including Nvidia NeMo, Nvidia NIM microservices and AI Blueprints. The AI Refinery for Industry solutions -- powered by Accenture AI Refinery with Nvidia -- can help enterprises rapidly launch agentic AI across fields like automotive, technology, manufacturing, consumer goods and more. Agentic AI Orchestration Tools Conduct a Symphony of Agents Agentic AI represents the next wave in the evolution of generative AI. It enables applications to move beyond simple chatbot interactions to tackle complex, multi-step problems through sophisticated reasoning and planning. As explained in Huang's CES keynote, enterprise AI agents will become a centerpiece of AI factories that generate tokens to create unprecedented intelligence and productivity across industries. Agentic AI orchestration is a sophisticated system designed to manage, monitor and coordinate multiple AI agents working together -- key to developing reliable enterprise agentic AI systems. The agentic AI orchestration layer from Nvidia partners provides the glue needed for AI agents to effectively work together. The new partner blueprints, now available from agentic AI orchestration leaders, offer integrations with Nvidia AI Enterprise software, including NIM microservices and Nvidia NeMo Retriever, to boost retrieval accuracy and reduce latency. For example: ● CrewAI is using new Llama 3.3 70B Nvidia NIM microservices and the Nvidia NeMo Retriever embedding NIM microservice for its blueprint for code documentation for software development. The blueprint helps ensure code repositories remain comprehensive and easy to navigate. ● Daily's voice agent blueprint, powered by the company's open-source Pipecat framework, uses the Nvidia Riva automatic speech recognition and text-to-speech NIM microservice, along with the Llama 3.3 70B NIM microservice to achieve real-time conversational AI. ● LangChain is adding Llama 3.3 70B Nvidia NIM microservices to its structured report generation blueprint. Built on LangGraph, the blueprint allows users to define a topic and specify an outline to guide an agent in searching the web for relevant information, so it can return a report in the requested format. ● LlamaIndex's document research assistant for blog creation blueprint harnesses Nvidia NIM microservices and NeMo Retriever to help content creators produce high-quality blogs. It can tap into agentic-driven retrieval-augumented generation with NeMo Retriever to automatically research, outline and generate compelling content with source attribution. ● Weights & Biases is adding its W&B Weave capability to the AI Blueprint for AI virtual assistants, which features the Llama 3.1 70B NIM microservice. The blueprint can streamline the process of debugging, evaluating, iterating and tracking production performance and collecting human feedback to support seamless integration and faster iterations for building and deploying agentic AI applications. Summarize Many, Complex PDFs While Keeping Proprietary Data Secure With trillions of PDF files -- from financial reports to technical research papers -- generated every year, it's a constant challenge to stay up to date with information. Nvidia's PDF to podcast AI Blueprint provides a recipe developers can use to turn multiple long and complex PDFs into AI-generated readouts that can help professionals, students and researchers efficiently learn about virtually any topic and quickly understand key takeaways. The blueprint -- built on NIM microservices and text-to-speech models -- allows developers to build applications that extract images, tables and text from PDFs, and convert the data into easily digestible audio content, all while keeping data secure. For example, developers can build AI agents that can understand context, identify key points and generate a concise summary as a monologue or a conversation-style podcast, narrated in a natural voice. This offers users an engaging, time-efficient way to absorb information at their desired speed. Test, Prototype and Run Agentic AI Blueprints in One Click Nvidia Blueprints empower the world's more than 25 million software developers to easily integrate AI into their applications across various industries. These blueprints simplify the process of building and deploying agentic AI applications, making advanced AI integration more accessible than ever. With just a single click, developers can now build and run the new agentic AI Blueprints as Nvidia Launchables. These Launchables provide on-demand access to developer environments with predefined configurations, enabling quick workflow setup. By containing all necessary components for development, Launchables support consistent and reproducible setups without the need for manual configuration or overhead -- streamlining the entire development process, from prototyping to deployment. Enterprises can also deploy blueprints into production with the Nvidia AI Enterprise software platform on data center platforms including Dell Technologies, Hewlett Packard Enterprise, Lenovo and Supermicro, or run them on accelerated cloud platforms from Amazon Web Services, Google Cloud, Microsoft Azure and Oracle Cloud Infrastructure. Accenture and Nvidia Fast-Track Deployments With AI Refinery for Industry Accenture is introducing new AI Refinery for Industry with 12 new industry agent solutions built with Nvidia AI Enterprise software and available from the Accenture Nvidia Business Group. These industry-specific agent solutions include public sector recruiting, agent-assist contact center for telecommunications, insurance claims underwriting, legacy modernization for banking, revenue growth management for consumer goods and services, clinical trial companion for life sciences, industrial asset troubleshooting and B2B marketing, among others. AI Refinery for Industry offerings include pre-configured components, best practices and foundational elements designed to fast-track the development of AI agents. They provide organizations the tools to build specialized AI networks tailored to their industry needs. Accenture plans to launch over 100 AI Refinery for Industry agent solutions by the end of the year.

Nvidia is jumping on the agentic AI bandwagon with new "blueprints" to simplify work

Five partner blueprints and additional in-house tools to launch first Nvidia has unveiled plans to get on board with the growing field of agentic AI applications at CES 2025. In a blog post, VP for Enterprise AI Justin Boitano described the company's new Nvidia AI Blueprints AI agents as "knowledge robots" with reasoning, planning and action-taking abilities. As AI adoption continues to grow, the prospect of more autonomous artificial intelligence boosts the technology's productivity benefits even further. Nvidia's early entry to the AI chip market has already seen share prices skyrocket, and an early entry to the agentic AI world could further that. Boitano confirmed some of the companies Nvidia partnered with to build the blueprints into the Nvidia AI Enterprise software platform; they include CrewAI, Daily, LangChain, LlamaIndex and Weights & Biases. He went on to describe agentic AI as "the next wave in the evolution of generative AI," sharing how they can tackle complex, multi-step problems that current chatbots struggle to do. Some of the earliest blueprints to launch include a code documentation tool for software development by Crew AI, real-time conversational AI by Daily and web searching by LangChain. All three use the new Llama 3.3 70B Nvidia NIM microservice. A blueprint for document research assistant for blog creation by LlamaIndex and a final one by Weights & Biases for debugging, evaluating, iterating and tracking production performance round up the five early-launch blueprints. Besides partner-supported blueprints, Nvidia has also launched its own - a PDF-to-podcast tool and one to build AI agents for video search and summarization, plus four Nvidia Omniverse blueprints for building simulation-ready digital twins. In just seven days since the beginning of 2025, Nvidia shares are up 9.93% as investors continue to be satisfied with performance. With a $3.659 trillion market cap, it comes second only to Apple, valued at $3.703 trillion.

NVIDIA and Partners Launch Agentic AI Blueprints to Automate Work for Every Enterprise

Developers can now build and deploy custom AI agents that can reason, plan and take action with new NVIDIA AI Blueprints that include NVIDIA NIM microservices, NVIDIA NeMo and agentic AI frameworks from leading providers. New NVIDIA AI Blueprints for building agentic AI applications are poised to help enterprises everywhere automate work. With the blueprints, developers can now build and deploy custom AI agents. These AI agents act like "knowledge robots" that can reason, plan and take action to quickly analyze large quantities of data, summarize and distill real-time insights from video, PDF and other images. CrewAI, Daily, LangChain, LlamaIndex and Weights & Biases are among leading providers of agentic AI orchestration and management tools that have worked with NVIDIA to build blueprints that integrate the NVIDIA AI Enterprise software platform, including NVIDIA NIM microservices and NVIDIA NeMo, with their platforms. These five blueprints -- comprising a new category of partner blueprints for agentic AI -- provide the building blocks for developers to create the next wave of AI applications that will transform every industry. In addition to the partner blueprints, NVIDIA is introducing its own new AI Blueprint for PDF to podcast, as well as another to build AI agents for video search and summarization. These are joined by four additional NVIDIA Omniverse Blueprints that make it easier for developers to build simulation-ready digital twins for physical AI. To help enterprises rapidly take AI agents into production, Accenture is announcing AI Refinery for Industry built with NVIDIA AI Enterprise, including NVIDIA NeMo, NVIDIA NIM microservices and AI Blueprints. The AI Refinery for Industry solutions -- powered by Accenture AI Refinery with NVIDIA -- can help enterprises rapidly launch agentic AI across fields like automotive, technology, manufacturing, consumer goods and more. Agentic AI Orchestration Tools Conduct a Symphony of Agents Agentic AI represents the next wave in the evolution of generative AI. It enables applications to move beyond simple chatbot interactions to tackle complex, multi-step problems through sophisticated reasoning and planning. As explained in NVIDIA founder and CEO Jensen Huang's CES keynote, enterprise AI agents will become a centerpiece of AI factories that generate tokens to create unprecedented intelligence and productivity across industries. Agentic AI orchestration is a sophisticated system designed to manage, monitor and coordinate multiple AI agents working together -- key to developing reliable enterprise agentic AI systems. The agentic AI orchestration layer from NVIDIA partners provides the glue needed for AI agents to effectively work together. The new partner blueprints, now available from agentic AI orchestration leaders, offer integrations with NVIDIA AI Enterprise software, including NIM microservices and NVIDIA NeMo Retriever, to boost retrieval accuracy and reduce latency of agent workflows. For example: Summarize Many, Complex PDFs While Keeping Proprietary Data Secure With trillions of PDF files -- from financial reports to technical research papers -- generated every year, it's a constant challenge to stay up to date with information. NVIDIA's PDF to podcast AI Blueprint provides a recipe developers can use to turn multiple long and complex PDFs into AI-generated readouts that can help professionals, students and researchers efficiently learn about virtually any topic and quickly understand key takeaways. The blueprint -- built on NIM microservices and text-to-speech models -- allows developers to build applications that extract images, tables and text from PDFs, and convert the data into easily digestible audio content, all while keeping data secure. For example, developers can build AI agents that can understand context, identify key points and generate a concise summary as a monologue or a conversation-style podcast, narrated in a natural voice. This offers users an engaging, time-efficient way to absorb information at their desired speed. Test, Prototype and Run Agentic AI Blueprints in One Click NVIDIA Blueprints empower the world's more than 25 million software developers to easily integrate AI into their applications across various industries. These blueprints simplify the process of building and deploying agentic AI applications, making advanced AI integration more accessible than ever. With just a single click, developers can now build and run the new agentic AI Blueprints as NVIDIA Launchables. These Launchables provide on-demand access to developer environments with predefined configurations, enabling quick workflow setup. By containing all necessary components for development, Launchables support consistent and reproducible setups without the need for manual configuration or overhead -- streamlining the entire development process, from prototyping to deployment. Enterprises can also deploy blueprints into production with the NVIDIA AI Enterprise software platform on data center platforms including Dell Technologies, Hewlett Packard Enterprise, Lenovo and Supermicro, or run them on accelerated cloud platforms from Amazon Web Services, Google Cloud, Microsoft Azure and Oracle Cloud Infrastructure. Accenture and NVIDIA Fast-Track Deployments With AI Refinery for Industry Accenture is introducing its new AI Refinery for Industry with 12 new industry agent solutions built with NVIDIA AI Enterprise software and available from the Accenture NVIDIA Business Group. These industry-specific agent solutions include revenue growth management for consumer goods and services, clinical trial companion for life sciences, industrial asset troubleshooting and B2B marketing, among others. AI Refinery for Industry offerings include preconfigured components, best practices and foundational elements designed to fast-track the development of AI agents. They provide organizations the tools to build specialized AI networks tailored to their industry needs. Accenture plans to launch over 100 AI Refinery for Industry agent solutions by the end of the year.

Nvidia's AI agent play is here with new models, orchestration blueprints

Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More The industry's push into agentic AI continues, with Nvidia announcing several new services and models to facilitate the creation and deployment of AI agents. Today, Nvidia launched Nemotron, a family of models based on Meta's Llama and trained on the company's techniques and datasets. The company also announced new AI orchestration blueprints to guide AI agents. These latest releases bring Nvidia, a company more known for the hardware that powers the generative AI revolution, to the forefront of agentic AI development. Nemotron comes in three sizes: Nano, Super and Ultra. It also comes in two flavors: the Llama Nemotron for language tasks and the Cosmos Nemotron vision model for physical AI projects. The Llama Nemotron Nano has 4B parameters, the Super 49B parameters and the Ultra 253B parameters. All three work best for agentic tasks including "instruction following, chat, function calling, coding and math," according to the company. Rev Lebaredian, VP of Omniverse and simulation technology at Nvidia, said in a briefing with reporters that the three sizes are optimized for different Nvidia computing resources. Nano is for cost-efficient low latency applications on PC and edge devices, Super is for high accuracy and throughput on a single GPU and Ultra is for highest accuracy at data center scale. "AI agents are the digital workforce that will work for us and work with us, and so the Nemotron model family is for agentic AI," said Lebaredian. The Nemotron models are available as hosted APIs on Hugging Face and Nvidia's website. Nvidia said enterprises can access the models through its AI Enterprise software platform. AI agents became a big trend in 2024 as enterprises began exploring how to deploy agentic systems in their workflow. Many believe that momentum will continue this year. Companies like Salesforce, ServiceNow, AWS and Microsoft have all called agents the next wave of gen AI in enterprises. AWS has added multi-agent orchestration to Bedrock, while Salesforce released its Agentforce 2.0, bringing more agents to its customers. However, agentic workflows still need other infrastructure to work efficiently. One such infrastructure revolves around orchestration, or managing multiple agents crossing different systems. Orchestration blueprints Nvidia has also entered the emerging field of AI orchestration with its blueprints that guide agents through specific tasks. The company has partnered with several orchestration companies, including LangChain, LlamaIndex, CrewAI, Daily and Weights and Biases, to build blueprints on Nvidia AI Enterprise. Each orchestration framework has developed its own blueprint with Nvidia. For example, CrewAI created a blueprint for code documentation to ensure code repositories are easy to navigate. LangChain added Nvidia NIM microservices to its structured report generation blueprint to help agents return internet searches in different formats. "Making multiple agents work together smoothly or orchestration is key to deploying agentic AI," said Lebaredian. "These leading AI orchestration companies are integrating every Nvidia agentic building block, NIM, Nemo and Blueprints with their open-source agentic orchestration platforms." Nvidia's new PDF-to-podcast blueprint aims to compete with Google's NotebookLM by converting information from PDFs to audio. Another new blueprint will help build agents to search for and summarize videos. Lebaredian said Blueprints aims to help developers quickly deploy AI agents. To that end, Nvidia unveiled Nvidia Launchables, a platform that lets developers test, prototype and run blueprints in one click.

Nvidia launches blueprint for AI agents that can analyze video

The new Nvidia AI Blueprint powered by Metropolis lets organizations and individuals increase productivity and safety, and could even help Nvidia's CEO improve his fastball pitch. The next big moment in AI is in sight -- literally. Today, more than 1.5 billion enterprise level cameras deployed worldwide are generating roughly 7 trillion hours of video per year. Yet, only a fraction of it gets analyzed. It's estimated that less than 1% of video from industrial cameras is watched live by humans, meaning critical operational incidents can go largely unnoticed. This comes at a high cost. For example, manufacturers are losing trillions of dollars annually to poor product quality or defects that they could've spotted earlier, or even predicted, by using AI agents that can perceive, analyze and help humans take action. Interactive AI agents with built-in visual perception capabilities can serve as always-on video analysts, helping factories run more efficiently, bolster worker safety, keep track things are running smoothly and even up an athlete's game. To accelerate the creation of such agents, Nvidia today announced early access to a new version of the Nvidia AI Blueprint for video search and summarization. Built on top of the Nvidia Metropolis platform -- and now supercharged by Nvidia Cosmos Nemotron vision language models (VLMs), Nvidia Llama Nemotron large language models (LLMs) and Nvidia NeMo Retriever -- the blueprint provides developers with the tools to build and deploy AI agents that can analyze large quantities of video and image content. The blueprint integrates the Nvidia AI Enterprise software platform -- which includes Nvidia NIM microservices for VLMs, LLMs and advanced AI frameworks for retrieval-augmented generation -- to enable batch video processing that's 30 times faster than watching it in real time. The blueprint contains several agentic AI features -- such as chain-of-thought reasoning, task planning and tool calling -- that can help developers streamline the creation of powerful and diverse visual agents to solve a range of problems. AI agents with video analysis abilities can be combined with other agents with different skill sets to enable even more sophisticated agentic AI services. Enterprises have the flexibility to build and deploy their AI agents from the edge to the cloud. How Video Analyst AI Agents Can Help Industrial Businesses AI agents with visual perception and analysis skills can be fine-tuned to help businesses with industrial operations by: ● Increasing productivity and reducing waste: Agents can help ensure standard operating procedures are followed during complex industrial processes like product assembly. They can also be fine-tuned to carefully watch and understand nuanced actions, and the sequence in which they're implemented. ● Boosting asset management efficiency through better space utilization: Agents can help optimize inventory storage in warehouses by performing 3D volume estimation and centralizing understanding across various camera streams. ● Improving safety through auto-generation of incident reports and summaries: Agents can process huge volumes of video and summarize it into contextually informative reports of accidents. They can also help ensure personal protective equipment compliance in factories, improving worker safety in industrial settings. ● Preventing accidents and production problems: AI agents can identify atypical activity to quickly mitigate operational and safety risks, whether in a warehouse, factory or airport, or at an intersection or other municipal setting. ● Learning from the past: Agents can search through operations video archives, and relevant information from the past and use it to solve problems or create new processes. Video Analysts for Sports, Entertainment and More Another industry where video analysis AI agents stand to make a mark is sports -- a $500 billion market worldwide, with hundreds of billions in projected growth over the next several years. Coaches, teams and leagues -- whether professional or amateur -- rely on video analytics to evaluate and enhance player performance, prioritize safety and boost fan engagement through player analytics platforms and data visualization. With visually perceptive AI agents, athletes now have unprecedented access to deeper insights and opportunities for improvement. During his CES opening keynote, Nvidia's Huang demonstrated an AI video analytics agent that assessed the fastball pitching skills of an amateur baseball player compared with a professional's. Using video captured from the ceremonial first pitch that Huang threw for the San Francisco Giants baseball team, the video analytics AI agent was able to suggest areas for improvement. The $3 trillion media and entertainment industry is also poised to benefit from video analyst AI agents. Through the Nvidia Media2 initiative, these agents will help drive the creation of smarter, more tailored and more impactful content that can adapt to individual viewer preferences. Worldwide Adoption and Availability Partners from around the world are integrating the blueprint for building AI agents for video analysis into their own developer work flows, including Accenture, Infosys, Linker Vision, Pegatron, TATA Consultancy Services (TCS), Telit Cinterion and VAST.

Now See This: NVIDIA Launches Blueprint for AI Agents That Can Analyze Video

New NVIDIA AI Blueprint powered by Metropolis lets organizations and individuals increase productivity and safety, and could even help NVIDIA's CEO improve his fastball pitch. Today, more than 1.5 billion enterprise level cameras deployed worldwide are generating roughly 7 trillion hours of video per year. Yet, only a fraction of it gets analyzed. It's estimated that less than 1% of video from industrial cameras is watched live by humans, meaning critical operational incidents can go largely unnoticed. This comes at a high cost. For example, manufacturers are losing trillions of dollars annually to poor product quality or defects that they could've spotted earlier, or even predicted, by using AI agents that can perceive, analyze and help humans take action. Interactive AI agents with built-in visual perception capabilities can serve as always-on video analysts, helping factories run more efficiently, bolster worker safety, keep traffic running smoothly and even up an athlete's game. To accelerate the creation of such agents, NVIDIA today announced early access to a new version of the NVIDIA AI Blueprint for video search and summarization. Built on top of the NVIDIA Metropolis platform -- and now supercharged by NVIDIA Cosmos Nemotron vision language models (VLMs), NVIDIA Llama Nemotron large language models (LLMs) and NVIDIA NeMo Retriever -- the blueprint provides developers with the tools to build and deploy AI agents that can analyze large quantities of video and image content. The blueprint integrates the NVIDIA AI Enterprise software platform -- which includes NVIDIA NIM microservices for VLMs, LLMs and advanced AI frameworks for retrieval-augmented generation -- to enable batch video processing that's 30x faster than watching it in real time. The blueprint contains several agentic AI features -- such as chain-of-thought reasoning, task planning and tool calling -- that can help developers streamline the creation of powerful and diverse visual agents to solve a range of problems. AI agents with video analysis abilities can be combined with other agents with different skill sets to enable even more sophisticated agentic AI services. Enterprises have the flexibility to build and deploy their AI agents from the edge to the cloud. How Video Analyst AI Agents Can Help Industrial Businesses AI agents with visual perception and analysis skills can be fine-tuned to help businesses with industrial operations by: Video Analysts for Sports, Entertainment and More Another industry where video analysis AI agents stand to make a mark is sports -- a $500 billion market worldwide, with hundreds of billions in projected growth over the next several years. Coaches, teams and leagues -- whether professional or amateur -- rely on video analytics to evaluate and enhance player performance, prioritize safety and boost fan engagement through player analytics platforms and data visualization. With visually perceptive AI agents, athletes now have unprecedented access to deeper insights and opportunities for improvement. During his CES opening keynote, NVIDIA founder and CEO Jensen Huang demonstrated an AI video analytics agent that assessed the fastball pitching skills of an amateur baseball player compared with a professional's. Using video captured from the ceremonial first pitch that Huang threw for the San Francisco Giants baseball team, the video analytics AI agent was able to suggest areas for improvement. The $3 trillion media and entertainment industry is also poised to benefit from video analyst AI agents. Through the NVIDIA Media2 initiative, these agents will help drive the creation of smarter, more tailored and more impactful content that can adapt to individual viewer preferences. Worldwide Adoption and Availability Partners from around the world are integrating the blueprint for building AI agents for video analysis into their own developer workflows, including Accenture, Centific, Deloitte, EY, Infosys, Linker Vision, Pegatron, TATA Consultancy Services (TCS), Telit Cinterion and VAST. Apply for early access to the NVIDIA Blueprint for video search and summarization.