With NVIDIA’s full stack infrastructure and software, developers can build agents that move beyond simple automation to true goal-based reasoning. These agents can ingest massive streams of live data to independently negotiate bids, manage multistep cross-channel budget shifts, and orchestrate full-funnel customer journeys. By leveraging a continuous “data flywheel,” these systems learn from every interaction, allowing brands to maintain high-performance, 24/7 campaign execution that is both self-optimizing and brand-compliant at a global scale.
The Next Era of Advertising and Marketing
Accelerate AdTech and MarTech Innovations with AI.
Build, Deploy, and Scale Next-Generation AI-Powered Advertising and Marketing Applications
The advertising and marketing technology ecosystem is undergoing a profound shift as agents, generative AI, privacy regulations, and fragmented consumer attention upend traditional ways of planning, creating, activating, and measuring campaigns. In this rapidly evolving environment, brands, agencies, and advertising and marketing platforms are looking for infrastructure and models that can keep pace. NVIDIA equips AdTech and MarTech developers with full-stack infrastructure and software to build, deploy, and scale next-generation AI-powered advertising and marketing applications.
Use Cases
AI-Powered Advertising and Marketing Use Cases
Agentic Advertising and Marketing
Develop autonomous systems that reason, plan, and execute complex media workflows.
Real-Time Decisioning for AdTech
Power every bid with intelligence and accelerated compute.
Contextual Intelligence
Bridge the gap between surface metadata and deep semantic understanding.
Content Generation and Optimization
Generate brand-consistent experiences with AI.
Success Stories
AdTech and MarTech Success Stories
Learn how AdTech and MarTech companies are using AI to scale performance and drive real-time results.
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Resources
Explore AdTech and MarTech Resources
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Trainings
Frequently Asked Questions
Agents are autonomous systems that leverage NVIDIA’s full stack to go beyond simple automation, using goal-based reasoning to execute complex media workflows. These agents can ingest massive streams of live data to independently manage multistep tasks, from bid negotiation to orchestrating full-funnel customer journeys, NVIDIA NeMo Agent Toolkit enables developers to build agents that perform complex reasoning and execution.
NVIDIA’s full-stack platform accelerates the entire data lifecycle, from high-throughput engineering to the continuous training of specialized models. This infrastructure provides the compute density to handle millions of queries per second (QPS) and process billions of real-time bidding (RTB) signals at ultra-low latency to power ad intelligence with accelerated compute.
RTB is the immediate, per-impression auction of ad inventory, which requires ultra-low-latency compute for processing billions of signals. NVIDIA’s platform is engineered to address performance bottlenecks, such as low-latency requirements for RTB and scaling QPS ad bidding infrastructure.
Multimodal media intelligence uses accelerated computing and AI software to run large-scale models that analyze frames, audio, and accompanying text together for deep semantic understanding of content environments. This capability moves beyond basic keyword detection to allow for precise contextual personalization, safer brand adjacencies, and accurate brand suitability scoring.
3D digital twins serve as the precise, ground-truth foundation for products, ensuring brand assets remain exact while generative AI freely adapts layouts, offers, and messaging. OpenUSD (Universal Scene Description) workflows, along with NVIDIA Omniverse libraries, are used to centralize these assets and create digital twins for content automation at scale using OpenUSD.
OpenUSD, or Universal Scene Description, is a critical technology used to establish centralized asset libraries and digital twins of products. This approach allows generative AI to adapt creative variations for hyper-personalization while ensuring that the underlying photorealistic product assets are always brand-accurate.
Demand-side platforms (DSPs), supply-side platforms (SSPs), and exchanges are three key components of the programmatic advertising ecosystem where inventory is bought and sold. NVIDIA’s platform provides compute density to optimize campaigns and enable more efficient investment across these platforms in the data science and predictive modeling section.
NVIDIA Omniverse and OpenUSD address slow, costly, and inconsistent manual localization processes by centralizing brand-accurate asset libraries in a unified approach. This method provides teams with instant access to photorealistic, brand-accurate assets through advanced 3D and AI workflows.
NVIDIA offers the AI Essentials Learning Series, expert-led courses, and workshops to help developers and IT professionals accelerate their careers and knowledge in AI. You can explore the resources available through the NVIDIA AI Essentials Learning Series for training in generative AI, data science, and accelerated graphics.
Generative AI is a form of artificial intelligence that creates new content, and in marketing, it is used to automatically adapt ad and digital content based on real-time signals, channels, and audience intent as a core technology in this shift. This ability to continuously adapt creative variations drives higher engagement, conversion, and media efficiency at scale.
NVIDIA provides full-stack infrastructure and software, including accelerated computing and specialized AI models, that enable companies to scale tasks from processing billions of RTB signals to deploying self-optimizing agentic systems. This infrastructure is designed to solve the most complex computational challenges, driving real-time results and shifting perception to view NVIDIA as an infrastructure and software partner.
Agentic systems learn from every interaction by leveraging a continuous “data flywheel” of massive streams of live data to achieve self-optimization. Brand compliance is maintained by embedding these constraints within the goal-based reasoning and execution frameworks of the autonomous systems.
Large-scale, multimodal models are enabled by NVIDIA’s accelerated computing and AI software stack to analyze frames, audio, and text together. These models are more powerful than traditional keyword detection and allow for a rich semantic understanding of media environments.
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