From NVIDIA: 2025-05-13 11:00:00

AI agents powered by large language models (LLMs) have evolved beyond basic chatbots to become advanced digital teammates capable of planning, reasoning, and taking action while receiving corrective feedback. These reasoning agents are transforming industries like customer service, healthcare, manufacturing, and financial services by tackling complex tasks efficiently.

Reasoning AI models allow agents to toggle reasoning on and off, optimizing the use of compute and tokens based on the complexity of the task. Industries are benefiting from reasoning agents for tasks like diagnostics in healthcare, personalized customer interactions in customer service, market analysis in finance, and logistics optimization.

New NVIDIA Llama Nemotron models with advanced reasoning capabilities offer developers the ability to enable or disable reasoning per query, saving time and costs for users. Companies like Amdocs, EY, and SAP are already utilizing reasoning agents to improve customer engagement, response quality, and business processes autonomously.

To build an AI reasoning agent, key components like tools, memory, and planning modules are required. Integrating reasoning capabilities into AI agents at various stages of development can enhance their ability to interact with the environment and execute plans effectively. The AI-Q NVIDIA AI Blueprint and NVIDIA Agent Intelligence toolkit help streamline workflows and optimize AI performance at scale.

Learn more about Llama Nemotron, a top-performing model for advanced tasks, and join the community shaping the future of reasoning-powered AI. Experiment with the Llama Nemotron post-training dataset to build custom reasoning agents and explore NIM-powered workflows for retrieval-augmented generation and video search and summarization to deploy advanced AI solutions efficiently.



Read more at NVIDIA: How Reasoning AI Agents Transform High-Stakes Decision Making