11 Integrations with NVIDIA Blueprints

View a list of NVIDIA Blueprints integrations and software that integrates with NVIDIA Blueprints below. Compare the best NVIDIA Blueprints integrations as well as features, ratings, user reviews, and pricing of software that integrates with NVIDIA Blueprints. Here are the current NVIDIA Blueprints integrations in 2026:

  • 1
    LangChain

    LangChain

    LangChain

    LangChain is a powerful, composable framework designed for building, running, and managing applications powered by large language models (LLMs). It offers an array of tools for creating context-aware, reasoning applications, allowing businesses to leverage their own data and APIs to enhance functionality. LangChain’s suite includes LangGraph for orchestrating agent-driven workflows, and LangSmith for agent observability and performance management. Whether you're building prototypes or scaling full applications, LangChain offers the flexibility and tools needed to optimize the LLM lifecycle, with seamless integrations and fault-tolerant scalability.
  • 2
    NVIDIA NIM
    Explore the latest optimized AI models, connect AI agents to data with NVIDIA NeMo, and deploy anywhere with NVIDIA NIM microservices. NVIDIA NIM is a set of easy-to-use inference microservices that facilitate the deployment of foundation models across any cloud or data center, ensuring data security and streamlined AI integration. Additionally, NVIDIA AI provides access to the Deep Learning Institute (DLI), offering technical training to gain in-demand skills, hands-on experience, and expert knowledge in AI, data science, and accelerated computing. AI models generate responses and outputs based on complex algorithms and machine learning techniques, and those responses or outputs may be inaccurate, harmful, biased, or indecent. By testing this model, you assume the risk of any harm caused by any response or output of the model. Please do not upload any confidential information or personal data unless expressly permitted. Your use is logged for security purposes.
  • 3
    NVIDIA NeMo
    NVIDIA NeMo LLM is a service that provides a fast path to customizing and using large language models trained on several frameworks. Developers can deploy enterprise AI applications using NeMo LLM on private and public clouds. They can also experience Megatron 530B—one of the largest language models—through the cloud API or experiment via the LLM service. Customize your choice of various NVIDIA or community-developed models that work best for your AI applications. Within minutes to hours, get better responses by providing context for specific use cases using prompt learning techniques. Leverage the power of NVIDIA Megatron 530B, one of the largest language models, through the NeMo LLM Service or the cloud API. Take advantage of models for drug discovery, including in the cloud API and NVIDIA BioNeMo framework.
  • 4
    NVIDIA AI Enterprise
    The software layer of the NVIDIA AI platform, NVIDIA AI Enterprise accelerates the data science pipeline and streamlines development and deployment of production AI including generative AI, computer vision, speech AI and more. With over 50 frameworks, pretrained models and development tools, NVIDIA AI Enterprise is designed to accelerate enterprises to the leading edge of AI, while also simplifying AI to make it accessible to every enterprise. The adoption of artificial intelligence and machine learning has gone mainstream, and is core to nearly every company’s competitive strategy. One of the toughest challenges for enterprises is the struggle with siloed infrastructure across the cloud and on-premises data centers. AI requires their environments to be managed as a common platform, instead of islands of compute.
  • 5
    NVIDIA Omniverse
    NVIDIA Omniverse™ acts as a hub to interconnect your existing 3D workflow, replacing linear pipelines with live-sync creation, letting you create like never before, and at speeds you’ve never experienced. Watch GeForce RTX 3D creators collaboratively create an animated short with Omniverse Cloud, bringing in 3D assets from their favorite design and content creation tools such as Autodesk Maya, Adobe Substance Painter, Unreal Engine, and SideFX Houdini. NVIDIA Omniverse enables Sir Wade Neistadt, who works in a variety of apps, to create without bottlenecks. Pairing the Omniverse Platform with an NVIDIA RTX™ A6000 running on NVIDIA Studio Drivers enables him to, as he states, ”put it all together, light it, render it, and have everything in context using RTX rendering—all without ever exporting the data to and from applications.
  • 6
    NVIDIA AI Foundations
    Impacting virtually every industry, generative AI unlocks a new frontier of opportunities, for knowledge and creative workers, to solve today’s most important challenges. NVIDIA is powering generative AI through an impressive suite of cloud services, pre-trained foundation models, as well as cutting-edge frameworks, optimized inference engines, and APIs to bring intelligence to your enterprise applications. NVIDIA AI Foundations is a set of cloud services that advance enterprise-level generative AI and enable customization across use cases in areas such as text (NVIDIA NeMo™), visual content (NVIDIA Picasso), and biology (NVIDIA BioNeMo™). Unleash the full potential with NeMo, Picasso, and BioNeMo cloud services, powered by NVIDIA DGX™ Cloud, the AI supercomputer. Marketing copy, storyline creation, and global translation in many languages. For news, email, meeting minutes, and information synthesis.
  • 7
    LlamaIndex

    LlamaIndex

    LlamaIndex

    LlamaIndex is a “data framework” to help you build LLM apps. Connect semi-structured data from API's like Slack, Salesforce, Notion, etc. LlamaIndex is a simple, flexible data framework for connecting custom data sources to large language models. LlamaIndex provides the key tools to augment your LLM applications with data. Connect your existing data sources and data formats (API's, PDF's, documents, SQL, etc.) to use with a large language model application. Store and index your data for different use cases. Integrate with downstream vector store and database providers. LlamaIndex provides a query interface that accepts any input prompt over your data and returns a knowledge-augmented response. Connect unstructured sources such as documents, raw text files, PDF's, videos, images, etc. Easily integrate structured data sources from Excel, SQL, etc. Provides ways to structure your data (indices, graphs) so that this data can be easily used with LLMs.
  • 8
    CrewAI

    CrewAI

    CrewAI

    CrewAI is a leading multi-agent platform that enables organizations to streamline workflows across various industries by building and deploying automated processes using any Large Language Model (LLM) and cloud platform. It offers a comprehensive suite of tools, including a framework and UI Studio, to facilitate the rapid development of multi-agent automations, catering to both coding professionals and those seeking no-code solutions. The platform supports flexible deployment options, allowing users to move their created 'crews'—teams of AI agents—to production with confidence, utilizing powerful tools for different deployment types and autogenerated user interfaces. CrewAI also provides robust monitoring capabilities, enabling users to track the performance and progress of their AI agents on both simple and complex tasks. Additionally, it offers testing and training tools to continually enhance the efficiency and quality of outcomes produced by these AI agents.
  • 9
    Accenture AI Refinery
    Accenture's AI Refinery is a comprehensive platform designed to help organizations rapidly build and deploy AI agents to enhance their workforce and address industry-specific challenges. The platform offers a collection of industry agent solutions, each codified with business workflows and industry expertise, enabling companies to customize these agents with their own data. This approach reduces the time to build and derive value from AI agents from months or weeks to days. AI Refinery integrates digital twins, robotics, and domain-specific models to optimize manufacturing, logistics, and quality through advanced AI, simulations, and collaboration in Omniverse, enabling autonomy, efficiency, and cost reduction across operations and engineering processes. The platform is built with NVIDIA AI Enterprise software, including NVIDIA NeMo, NVIDIA NIM microservices, and NVIDIA AI Blueprints, such as video search, summarization, and digital human.
  • 10
    NVIDIA AI Data Platform
    ​NVIDIA's AI Data Platform is a comprehensive solution designed to accelerate enterprise storage and optimize AI workloads, facilitating the development of agentic AI applications. It integrates NVIDIA Blackwell GPUs, BlueField-3 DPUs, Spectrum-X networking, and NVIDIA AI Enterprise software to enhance performance and accuracy in AI workflows. NVIDIA AI Data Platform optimizes workload distribution across GPUs and nodes, leveraging intelligent routing, load balancing, and advanced caching to enable scalable, complex AI processes. This infrastructure supports the deployment and scaling of AI agents across hybrid data centers, transforming raw data into actionable insights in real-time. ​With the platform, enterprises can process and extract insights from structured or unstructured data, unlocking valuable insights from all available data sources, text, PDF, images, and video.
  • 11
    NVIDIA Llama Nemotron
    ​NVIDIA Llama Nemotron is a family of advanced language models optimized for reasoning and a diverse set of agentic AI tasks. These models excel in graduate-level scientific reasoning, advanced mathematics, coding, instruction following, and tool calls. Designed for deployment across various platforms, from data centers to PCs, they offer the flexibility to toggle reasoning capabilities on or off, reducing inference costs when deep reasoning isn't required. The Llama Nemotron family includes models tailored for different deployment needs. Built upon Llama models and enhanced by NVIDIA through post-training, these models demonstrate improved accuracy, up to 20% over base models, and optimized inference speeds, achieving up to five times the performance of other leading open reasoning models. This efficiency enables handling more complex reasoning tasks, enhances decision-making capabilities, and reduces operational costs for enterprises. ​
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