NVIDIA NeMo Tools Help Enterprises Boost AI Agent Productivity with Data Flywheels
PorAinvest
jueves, 24 de abril de 2025, 11:54 am ET2 min de lectura
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NeMo microservices, deployed via Nvidia's AI Enterprise software platform, provide a comprehensive end-to-end developer platform for creating state-of-the-art agentic AI systems. They include tools for data curation, customization, evaluation, and guardrails, ensuring that AI agents stay on topic and avoid missteps around content, safety, and security. The platform supports a wide range of models, including Meta’s Llama, Google Gemma, Mistral, Microsoft’s Phi, and Nvidia’s Llama Nemotron Ultra AI reasoning model.
The data flywheel process is central to NeMo microservices. It involves continuously feeding data from inference, business intelligence, and user feedback back into the AI system to improve its understanding and capabilities. This cycle ensures that AI agents remain accurate and up-to-date, learning from their experiences and growing with new skills and knowledge.
NVIDIA has already partnered with several high-profile companies, such as AT&T, Cisco, and Cloudera, to leverage NeMo microservices for various applications. AT&T, for example, has built an AI agent to process a knowledge base of almost 10,000 documents, while Cisco's Outshift emerging tech unit is using NeMo microservices to develop a coding assistant with improved response time and reduced tool selection errors.
The microservices are designed to work seamlessly with other NeMo tools, making it easier for enterprises to build, optimize, and scale AI agents through custom enterprise data flywheels. NVIDIA expects its efforts in this area to grow, both in terms of functionality and industry adoption. The company is committed to helping partners collect the right information and feed it back into the data flywheel, driving continuous improvement in AI systems.
In summary, NVIDIA NeMo microservices represent a significant advancement in enterprise AI, offering a robust platform for building and optimizing AI teammates. By leveraging the power of data flywheels, these microservices promise to enhance AI agent accuracy, productivity, and reliability, making them invaluable assets for businesses worldwide.
References:
[1] https://www.nextplatform.com/2025/04/23/nvidia-nemo-microservices-for-ai-agents-hits-the-market/
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NVIDIA NeMo microservices are now generally available, helping enterprises quickly build AI teammates that tap into data flywheels to scale employee productivity. The microservices provide an end-to-end developer platform for creating state-of-the-art agentic AI systems and continually optimizing them with data flywheels informed by inference and business data, as well as user preferences. They speed AI agent development with tools for curating, customizing, evaluating and guardrailing models, and can be used alongside other NeMo tools to ease experiences building, optimizing and scaling AI agents through custom enterprise data flywheels.
NVIDIA has announced the general availability of its NeMo microservices, a powerful toolset designed to help enterprises build and optimize AI teammates. These microservices leverage the concept of a data flywheel, a continuous learning cycle that improves AI applications through exposure to enterprise data and user interactions. This innovative approach aims to enhance the accuracy and productivity of AI agents, making them valuable partners for millions of workers worldwide.NeMo microservices, deployed via Nvidia's AI Enterprise software platform, provide a comprehensive end-to-end developer platform for creating state-of-the-art agentic AI systems. They include tools for data curation, customization, evaluation, and guardrails, ensuring that AI agents stay on topic and avoid missteps around content, safety, and security. The platform supports a wide range of models, including Meta’s Llama, Google Gemma, Mistral, Microsoft’s Phi, and Nvidia’s Llama Nemotron Ultra AI reasoning model.
The data flywheel process is central to NeMo microservices. It involves continuously feeding data from inference, business intelligence, and user feedback back into the AI system to improve its understanding and capabilities. This cycle ensures that AI agents remain accurate and up-to-date, learning from their experiences and growing with new skills and knowledge.
NVIDIA has already partnered with several high-profile companies, such as AT&T, Cisco, and Cloudera, to leverage NeMo microservices for various applications. AT&T, for example, has built an AI agent to process a knowledge base of almost 10,000 documents, while Cisco's Outshift emerging tech unit is using NeMo microservices to develop a coding assistant with improved response time and reduced tool selection errors.
The microservices are designed to work seamlessly with other NeMo tools, making it easier for enterprises to build, optimize, and scale AI agents through custom enterprise data flywheels. NVIDIA expects its efforts in this area to grow, both in terms of functionality and industry adoption. The company is committed to helping partners collect the right information and feed it back into the data flywheel, driving continuous improvement in AI systems.
In summary, NVIDIA NeMo microservices represent a significant advancement in enterprise AI, offering a robust platform for building and optimizing AI teammates. By leveraging the power of data flywheels, these microservices promise to enhance AI agent accuracy, productivity, and reliability, making them invaluable assets for businesses worldwide.
References:
[1] https://www.nextplatform.com/2025/04/23/nvidia-nemo-microservices-for-ai-agents-hits-the-market/

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