How NVIDIA’s AI Inference Platform is Powering Profitable AI Across Industries
Businesses across every industry are rapidly adopting AI services to drive innovation, improve efficiency, and enhance user experiences. For leading companies like Microsoft, Oracle, Perplexity, Snap, and hundreds of others, the NVIDIA AI inference platform has become a cornerstone for delivering high-throughput, low-latency AI inference at scale. This full-stack solution—comprising world-class silicon, systems, and software—enables organizations to deploy cutting-edge generative AI models while optimizing costs and energy efficiency.
The NVIDIA Hopper platform, with advancements in inference software optimization, delivers up to 15x more energy efficiency for inference workloads compared to previous generations. These innovations are helping industries serve the latest large language models (LLMs) and other AI applications, ensuring excellent user experiences while reducing total cost of ownership (TCO). At the heart of this success lies a simple yet critical goal: generate more tokens at a lower cost. Tokens, which represent words in LLM systems, directly impact the profitability of AI investments, as inference services typically charge per million tokens generated.
Full-Stack Optimization: The Key to Cost-Effective AI Inference
AI inference is notoriously complex, requiring a delicate balance between throughput, latency, and user experience. However, NVIDIA’s full-stack software optimization simplifies this process, enabling businesses to achieve higher performance and lower costs. NVIDIA offers a suite of tools tailored to meet diverse AI inference needs:
- NVIDIA NIM Microservices: Prepackaged and performance-optimized for rapid deployment of AI foundation models on any infrastructure—cloud, data centers, edge, or workstations.
- NVIDIA Triton Inference Server: A popular open-source project that allows users to package and serve any model, regardless of the AI framework it was trained on.
- NVIDIA TensorRT: A high-performance deep learning inference library that includes runtime and model optimizations to deliver low-latency, high-throughput inference for production applications.
These solutions are available through the NVIDIA AI Enterprise software platform, which provides enterprise-grade support, stability, manageability, and security. By leveraging NVIDIA’s framework-agnostic platform, companies save on productivity, development, and infrastructure costs while unlocking new revenue streams through AI-powered services.
Cloud-Based LLM Inference: Seamless Deployment Across Major Cloud Providers
To simplify LLM deployment, NVIDIA has collaborated closely with major cloud service providers, ensuring seamless integration with minimal or no code required. NVIDIA NIM microservices and Triton Inference Server are deeply integrated into platforms like:
- Amazon SageMaker AI, Amazon Bedrock Marketplace, and Amazon Elastic Kubernetes Service (EKS)
- Google Cloud’s Vertex AI and Google Kubernetes Engine (GKE)
- Microsoft Azure AI Foundry (coming soon) and Azure Kubernetes Service (AKS)
- Oracle Cloud Infrastructure (OCI) data science tools and OCI Kubernetes Engine
For example, deploying NVIDIA Triton on Oracle Cloud Infrastructure (OCI) is as simple as enabling a switch during model deployment, instantly launching an inference endpoint. Similarly, Azure Machine Learning supports both no-code and full-code deployments of NVIDIA Triton, while AWS and Google Cloud offer one-click deployment options for NVIDIA solutions.
This flexibility ensures businesses can scale their AI workloads efficiently, adapting to growing demands within cloud-based infrastructures.
Real-World Impact: Transforming Industries with NVIDIA AI Inference
Perplexity AI: Serving 400 Million Search Queries Monthly
Perplexity AI, an AI-powered search engine handling over 435 million monthly queries, relies on NVIDIA H100 GPUs, Triton Inference Server, and TensorRT-LLM to manage its workload. Supporting over 20 AI models, including variations of Llama 3, Perplexity uses smaller classifier models to route tasks to GPU pods, achieving a threefold cost reduction while maintaining low latency and high accuracy.
Docusign: Revolutionizing Agreement Management
Docusign, a leader in digital agreement management, adopted NVIDIA Triton to supercharge its Intelligent Agreement Management platform. By using Triton as a unified inference server for all AI frameworks, Docusign accelerated time to market and transformed agreement data into actionable insights, enhancing customer experiences and operational efficiency.
Amdocs: Enhancing Telco Customer Care
Amdocs, a provider of software and services for communications and media companies, used NVIDIA DGX Cloud and AI Enterprise software to build amAIz, a domain-specific generative AI platform for telcos. By leveraging NVIDIA NIM, Amdocs reduced token consumption by up to 60% in data preprocessing and 40% in inferencing, while slashing query latency by approximately 80%, ensuring near real-time responses.
Snap: Revolutionizing Retail with Screenshop
Snap’s Screenshop feature, integrated into Snapchat, helps users find fashion items from photos. NVIDIA Triton enabled Snap to consolidate its pipeline onto a single inference serving platform, reducing development time and costs. By adopting NVIDIA TensorRT, Snap achieved a 3x surge in throughput and a 66% cost reduction.
Wealthsimple: Empowering Financial Services
Wealthsimple, a Canadian investment platform managing over C$30 billion in assets, standardized its infrastructure with NVIDIA Triton, reducing model delivery time from months to under 15 minutes. This transformation ensured 99.999% uptime, enabling seamless predictions for over 145 million transactions annually.
Let’s Enhance: Elevating Creative Workflows
Let’s Enhance, an AI startup, leveraged NVIDIA Triton to integrate the Stable Diffusion XL model into its workflows. With Triton’s dynamic batching and robust framework support, the company streamlined its AI pipelines, freeing engineering teams to focus on research and development.
Oracle Cloud Infrastructure (OCI): Accelerating Vision AI
OCI integrated NVIDIA Triton to power its Vision AI service, enhancing prediction throughput by 76% and reducing latency by 51%. These optimizations improved customer experiences in applications like toll billing automation and invoice recognition.
Microsoft: Real-Time Contextualized Intelligence
NVIDIA GPUs and Triton accelerate AI inference in Copilot for Microsoft 365, delivering real-time contextualized intelligence. Additionally, Microsoft Bing used NVIDIA TensorRT-LLM techniques to significantly improve inference performance for its Deep Search feature.
