{"id":3963,"date":"2025-04-15T01:41:33","date_gmt":"2025-04-15T01:41:33","guid":{"rendered":"https:\/\/salarydistribution.com\/machine-learning\/2025\/04\/15\/nvidia-unveils-ai-q-blueprint-to-connect-ai-agents-for-the-future-of-work\/"},"modified":"2025-04-15T01:41:33","modified_gmt":"2025-04-15T01:41:33","slug":"nvidia-unveils-ai-q-blueprint-to-connect-ai-agents-for-the-future-of-work","status":"publish","type":"post","link":"https:\/\/salarydistribution.com\/machine-learning\/2025\/04\/15\/nvidia-unveils-ai-q-blueprint-to-connect-ai-agents-for-the-future-of-work\/","title":{"rendered":"NVIDIA Unveils AI-Q Blueprint to Connect AI Agents for the Future of Work"},"content":{"rendered":"
\n\t\t<\/span> <\/span> <\/span><\/span><\/p>\n

AI agents<\/a> are the new digital workforce, transforming business operations, automating complex tasks and unlocking new efficiencies. Now, with the ability to collaborate, these agents can work together to solve complex problems and drive even greater impact.<\/p>\n

Businesses across industries, including sports and finance, can more quickly harness these benefits with AI-Q<\/a> \u2014 a new NVIDIA Blueprint<\/a> for developing agentic systems that can use reasoning to unlock knowledge in enterprise data.<\/p>\n

Smarter Agentic AI Systems With NVIDIA AI-Q and NVIDIA Agent Intelligence Toolkit<\/b><\/h2>\n

AI-Q provides an easy-to-follow reference for integrating NVIDIA accelerated computing, partner storage platforms, and software and tools \u2014 including the new NVIDIA Llama Nemotron reasoning models<\/a>. AI-Q offers a powerful foundation for enterprises to build digital workforces that break down agentic silos and are capable of handling complex tasks with high accuracy and speed.<\/p>\n

\"\"<\/p>\n

AI-Q integrates fast multimodal extraction and world-class retrieval, using NVIDIA NeMo Retriever<\/a>, NVIDIA NIM<\/a> microservices and AI agents.<\/p>\n

The blueprint is powered by the new NVIDIA Agent Intelligence toolkit<\/a> for seamless, heterogeneous connectivity between agents, tools and data. Released today on GitHub<\/a>, Agent Intelligence is an open-source software library for connecting, profiling and optimizing teams of AI agents fueled by enterprise data to create multi-agent, end-to-end systems<\/a>. It can be easily integrated with existing multi-agent systems \u2014 either in parts or as a complete solution \u2014 with a simple onboarding process that\u2019s 100% opt-in.<\/p>\n

The Agent Intelligence toolkit also enhances transparency with full system traceability and profiling \u2014 enabling organizations to monitor performance, identify inefficiencies and gain fine-grained understanding of how business intelligence is generated. This profiling data can be used with NVIDIA NIM and the NVIDIA Dynamo<\/a> open-source library to optimize the performance of agentic systems.<\/p>\n

The New Enterprise AI Agent Workforce<\/b><\/h2>\n

As AI agents become digital employees, IT teams will support onboarding and training. The AI-Q blueprint and Agent Intelligence toolkit support digital employees by enabling collaboration between agents and optimizing performance across different agentic frameworks.<\/p>\n

Enterprises using these tools will be able to more easily connect AI agent teams across solutions \u2014 like Salesforce\u2019s Agentforce, Atlassian Rovo in Confluence and Jira, and the ServiceNow AI platform for business transformation \u2014 to break down silos, streamline tasks and cut response times from days to hours.<\/p>\n

Agent Intelligence also integrates with frameworks and tools like CrewAI, LangGraph, Llama Stack, Microsoft Azure AI Agent Service and Letta, letting developers work in their preferred environment.<\/p>\n

Azure AI Agent Service is integrated with Agent Intelligence to enable more efficient AI agents and orchestration of multi-agent frameworks using Semantic Kernel, which is fully supported in Agent Intelligence.<\/p>\n

A wide range of industries are integrating visual perception and interactive capabilities into their agents and copilots.<\/p>\n

Financial services leader Visa is using AI agents to streamline cybersecurity, automating phishing email analysis at scale. Using the profiler feature of AI-Q, Visa can optimize agent performance and costs, maximizing AI\u2019s role in efficient threat response.<\/p>\n

Get Started With AI-Q and Agent Intelligence<\/b><\/h2>\n

AI-Q integration into the NVIDIA Metropolis VSS blueprint<\/a> is enabling multimodal agents, combining visual perception with speech, translation and data analytics for enhanced intelligence.<\/p>\n

Developers can use the Agent Intelligence toolkit<\/a> open-source library today and sign up for this hackathon<\/a> to build hands-on skills for advancing agentic systems.<\/p>\n

Plus, learn how<\/a> an NVIDIA solutions architect used the Agent Intelligence toolkit to improve AI code generation.<\/p>\n

Agentic systems built with AI-Q require a powerful AI data platform<\/a>. NVIDIA partners are delivering these customized platforms that continuously process data to let AI agents quickly access knowledge to reason and respond to complex queries.<\/p>\n

See <\/i>notice<\/i><\/a> regarding software product information.<\/i><\/p>\n<\/p><\/div>\n","protected":false},"excerpt":{"rendered":"

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