AI agents 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.
Businesses across industries, including sports and finance, can more quickly harness these benefits with AI-Q — a new NVIDIA Blueprint for developing agentic systems that can use reasoning to unlock knowledge in enterprise data.
Smarter Agentic AI Systems With NVIDIA AI-Q and AgentIQ Toolkit
AI-Q provides an easy-to-follow reference for integrating NVIDIA accelerated computing, partner storage platforms, and software and tools — including the new NVIDIA Llama Nemotron reasoning models. 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.
AI-Q integrates fast multimodal extraction and world-class retrieval, using NVIDIA NeMo Retriever, NVIDIA NIM microservices and AI agents.
The blueprint is powered by the new NVIDIA AgentIQ toolkit for seamless, heterogeneous connectivity between agents, tools and data. Released today on GitHub, AgentIQ 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. It can be easily integrated with existing multi-agent systems — either in parts or as a complete solution — with a simple onboarding process that’s 100% opt-in.
The AgentIQ toolkit also enhances transparency with full system traceability and profiling — 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 open-source library to optimize the performance of agentic systems.
The New Enterprise AI Agent Workforce
As AI agents become digital employees, IT teams will support onboarding and training. The AI-Q blueprint and AgentIQ toolkit support digital employees by enabling collaboration between agents and optimizing performance across different agentic frameworks.
Enterprises using these tools will be able to more easily connect AI agent teams across solutions — like Salesforce’s Agentforce, Atlassian Rovo in Confluence and Jira, and the ServiceNow AI platform for business transformation — to break down silos, streamline tasks and cut response times from days to hours.
AgentIQ 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.
Azure AI Agent Service is integrated with AgentIQ to enable more efficient AI agents and orchestration of multi-agent frameworks using Semantic Kernel, which is fully supported in AgentIQ.
A wide range of industries are integrating visual perception and interactive capabilities into their agents and copilots.
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’s role in efficient threat response.
Get Started With AI-Q and AgentIQ
AI-Q integration into the NVIDIA Metropolis VSS blueprint is enabling multimodal agents, combining visual perception with speech, translation and data analytics for enhanced intelligence.
Developers can use the AgentIQ toolkit open-source library today and sign up for this hackathon to build hands-on skills for advancing agentic systems.
Plus, learn how an NVIDIA solutions architect used the AgentIQ toolkit to improve AI code generation.
Agentic systems built with AI-Q require a powerful AI data platform. 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.
See notice regarding software product information.