NVIDIA AI Use Cases for MSPs: Enhance Efficiency and Offerings

Channel Insider content and product recommendations are editorially independent. We may make money when you click on links to our partners. Learn More.

Artificial intelligence (AI) and machine learning (ML) are indispensable drivers of operational efficiency, revolutionizing organizational operations across every conceivable sector of the economy. With its high-performing GPUs powering edge-to-cloud computing, supercomputers, and workstations, NVIDIA’s comprehensive suite of products, platforms, and solutions is the AI engine many MSPs are turning to to deliver superior business outcomes and become more resilient in supporting customers’ AI needs.

Specifically, MSPs can leverage NVIDIA’s integrated offering of hardware, software, tools, models, and APIs to provide an integrated AI platform for continuous modeling, DevSecOps, data analytics and inference, human-machine interactions, and more.

This article describes the top use cases for NVIDIA’s AI solutions and tools and how they can help MSPs become the IT backbone for accelerating customer innovation and growth.

Support enterprise-wide innovation with the AI platform

The NVIDIA AI Platform is designed to enhance enterprise-wide AI computing capabilities, providing full-stack innovation across accelerated infrastructure, enterprise-grade software, and AI models. MSPs can use its hardware, enterprise-grade software, and advanced AI models to expedite projects from inception to production while minimizing costs.

The platform includes the following:

• NVIDIA DGX Cloud for access to powerful supercomputing resources within leading cloud environments.
• Scalable, multi-node training models accessible via a web browser.
• A software layer that streamlines data science pipelines and facilitates the deployment of AI solutions in real-world settings.
• Pre-built models and services to create AI apps across text analysis and visual media processing domains.

By delivering advanced solutions to customers, MSPs can accelerate their enterprise AI workflow processes at a lower overall cost.

Help customers manage their complete AI needs as a DGX-Ready MSP

In the race to integrate AI and ML technologies for competitive advantage, organizations face the task of managing these advanced systems within their existing IT landscapes. This is where MSPs offering NVIDIA DGX-Ready Managed Services can give their customers a definitive leg up.

As an NVIDIA DGX-Ready Managed Services Partner, MSPs can provide customers with the expertise and resources to deploy, manage, and optimize their operations while achieving these two essential goals:

• Become the go-to for handling all aspects of AI for customers, freeing them from the burden of provisioning and maintenance so they can focus on their core strategic objectives.
• Empower customers to accelerate innovation, extract valuable AI insights, and maintain a competitive edge in the rapidly evolving AI landscape.

MSPs hoping to fill critical infrastructure customer skill gaps and become a one-stop-shop for Gen AI, data analytics workflows, machine learning, and modeling might consider partnering with NVIDIA as a certified DGX-Ready Managed Services provider.

Support massive inference requirements with the Triton Server

Part of NVIDIA’s AI platform, the Triton Inference Server facilitates AI model deployment with open-source support for various frameworks while providing direct integration into operational workflows with robust security.

Triton claims to ensure compatibility across TensorFlow, PyTorch, ONNX, and custom solutions to optimize efficiency, and is interoperational with diverse hardware, including NVIDIA GPUs and AWS Inferentia. Triton standardizes AI model deployment and executes across every workload, providing the following benefits:

• Supports high-volume inference needs across cloud, data center, edge, and embedded devices on NVIDIA GPUs, x86 and ARM CPU, or AWS Inferentia.
• Provides enterprise-grade security and API stability in a production-ready environment for value realization.
• Enables smooth integration with DevOps and MLOps platforms like Kubernetes and Prometheus.
• Facilitates large language model (LLM) inference with model ensembles to enhance efficiency.
• Uses the PyTriton framework to serve machine learning models with direct deployment from Python, simplifying workflows for Python developers.
• Optimizes configurations and boosts performance while minimizing resource consumption.
• Delivers high-speed performance for real-time, batched, and ensembled queries along with audio/video streaming.

These features can make Triton helpful to MSPs seeking to efficiently deploy and manage AI models for customers. This allows MSPs to accelerate their customers’ data science pipelines and speed development processes.

Speed DevSecOps with AI workflows

NVIDIA’s AI workflows, part of the NVIDIA AI platform, provide developers with cloud-native reference applications to expedite solution development. Leveraging NVIDIA’s AI software can help developers reduce their development and deployment timelines and securely implement DevOps.

NVIDIA’s AI workflows provide MSPs with the following uses:

• Leverages pre-trained AI models, training and inference pipelines, Jupyter Notebooks, and Helm charts.
• Prioritizes accuracy and performance with frameworks and containers meticulously optimized and tested for NVIDIA GPUs.
• Enables DevSecOps professionals to transition from pilot to production with top security, API stability, and comprehensive support.
• Speeds deployment of AI solutions across various domains, including intelligent virtual assistants, cybersecurity, route optimization, and retail analytics.

The cloud-native, prepackaged reference examples that are part of NVIDIA’s AI platform can help customers develop faster deployments and improve accuracy and performance. At the same time, they can enable MSPs to become a dominant player in the AI space.

Drive human-machine interactions with conversational AI solutions

NVIDIA’s conversational AI solutions encompass virtual assistants, digital humans, and chatbots. With these tools, developers at customer sites can construct and deploy advanced models that meet the stringent requirements of real-time interactions. Customers benefit from faster interactions between individuals and devices, machines, and computers, enhancing and streamlining daily activities.

NVIDIA’s suite of conversational AI solutions offers the following:

• Transcribes conversations with customers in real time.
• Enables audio content consumption for individuals with speech difficulties.
• Provides round-the-clock availability through chatbots.
• Supports resolution of end-user customer inquiries via captioning and synthetic voices.
• Provides automatic speech recognition (ASR) and text-to-speech (TTS).
• Converts spoken words into text and creates human-like voices from written text.
• Delivers advanced techniques for large language models (LLMs) and retrieval-augmented generation (RAG).

MSPs might use NVIDIA’s conversational AI solutions to enable their customers to deliver enhanced end-user customer support, add innovative accessibility features, and provide round-the-clock engagement. These valuable features help MSPs position themselves as leaders in facilitating human-machine interactions.

Enhance data usability with high-performance data analytics

NVIDIA’s high-performance data analytics engine offers comprehensive solutions to expedite the entire analytics workflow, whether for reducing processing times for extract, transform, load, (ETL) pipelines or scaling up large-scale machine learning tasks. Its data analytics workflows enable it to run seamlessly on everything from laptops to the cloud and on-premises, with the following user benefits:

• Enables iteration of large datasets and frequent model deployments with reduced run times and lower costs.
• Improves the accuracy of predictive analytics with less wait time, lower costs, and no refactoring.
• Integrates hardware and software solutions optimized for high-performance data analytics.
• Uses the RAPIDS open-source software suites and NVIDIA CUDA data practitioners to speed analytics pipelines on NVIDIA GPUs.
• Reduces loading, processing, and training time.
• Enables developers to use familiar languages like Python and Java.

MSPs can provide their customers with a high-performance data analytics engine that extracts actionable insights from their data repositories, speeds product development, and provides continuous innovation across user organizations. MSPs can also help customers deploy more models more frequently with faster times and reduced costs with the platform’s data analytics tools.

Boost generative AI with enterprise-ready APIs

NVIDIA’s fully integrated ecosystem of generative AI capabilities enables quick, easy deployment of advanced AI applications across user organizations. Organizations are equipped with a way to continuously develop solutions tailored to specific industry applications. They can harness the power of generative AI to drive enterprise-wide transformation and meet business objectives, irrespective of industry or company size.

The platform’s generative AI APIs provide numerous benefits, including the following:

• Enterprise-grade generative AI capabilities complete with tools, training, and technical resources for enterprise-ready APIs that run anywhere.
• Secure and scalable solutions and APIs that are optimized for performance and that integrate into any environment.
• Easy-to-implement processes that can be deployed across any sector — from healthcare, telecommunications, public services, and finance to retail, media, and entertainment — to enhance the customer experience and drive business growth. 

With the platform’s generative AI capabilities, MSPs can deliver functionality across every market segment, enabling customers to innovate and stay ahead.

Optimize machine learning within an advanced learning ecosystem

The platform’s optimized machine learning ecosystem is designed to increase model accuracy and positively impact customers’ bottom line. NVIDIA’s machine-learning infrastructure integrates low-latency hardware and software, eliminating the complexities associated with traditional machine-learning approaches.

Data scientists can iterate rapidly on features, leverage massive datasets for precise predictions, and quickly deploy value-generating solutions into their production environments. Data science teams can sidestep the computational bottlenecks and traditional prolonged cycle times while gaining the following:

• Access to an advanced machine learning ecosystem.
• Reduced processing wait times that allow for more time iterating and testing solutions.
• Processing speeds up to 19X faster than the CPU-based industry standard.
• Multi-terabyte datasets analytics with high-performance processing to drive higher accuracy and quicker reporting.
• Elimination of refactoring through acceleration and scaling of existing data science toolchains.
• Minimal code changes without the need to learn new tools.
• Integration with leading Apache Spark, cuPy, Dask, XGBoost, and Numba, as well as numerous deep learning frameworks, such as PyTorch, TensorFlow, and Apache MXNet, to broaden adoption.

MSPs can provide their customers with a way to avoid common machine-learning pain points while helping them unlock the full potential of their data. With NVIDIA’s AI platform, hardware and software are optimized so they can offer customers robust capabilities that enable data-driven insights for strategic decision-making.

Bottom line: Consider future-proofing your operations with NVIDIA’s AI solutions

If you can imagine benefiting from one or all of the use cases above, joining forces with NVIDIA can be a strategic way to achieve innovation, efficiency, and growth acceleration. The company’s suite of AI solutions helps organizations across every industry sector to drive business advancements. Its focus on scalability, efficiency, and performance caters to a wide range of application needs that can help organizations stay ahead of the curve while revolutionizing security.

As AI continues to transform the business landscape, MSPs must embrace certain technologies to remain competitive and meet the evolving needs of their customers. From AI-powered cybersecurity solutions to advanced visualization capabilities, NVIDIA offers a comprehensive ecosystem of products and services to MSPs under one roof.