NVIDIA Releases the NVIDIA AI-Q Blueprint to Link AI Agents for the Work of the Future. Business processes are incredibly productive and efficient because to Blueprint.
Artificial intelligence (AI) agents are the new digital workforce that is revolutionizing company processes by automating difficult jobs and generating new efficiencies. Now that they can cooperate, these agents can solve complicated issues and have an even bigger impact.
With AI-Q, a new NVIDIA Blueprint for creating agentic systems that can utilize reasoning to unlock knowledge in enterprise data, businesses in a variety of industries, including sports and finance, may more swiftly take advantage of these advantages.
Smarter Agentic AI Systems With NVIDIA AI-Q and AgentIQ Toolkit
More Intelligent Agentic AI Systems With NVIDIA AI-Q and AgentIQ Toolkit, AI-Q offers a simple guide for combining partner storage platforms, software, tools, and NVIDIA accelerated compute. Including the recently released Llama Nemotron reasoning models from NVIDIA. AI-Q provides businesses with a strong platform on which to develop digital workforces that can handle complicated jobs quickly and accurately while dismantling agentic silos.
With the use of NVIDIA NeMo Retriever, NVIDIA NIM microservices, and AI agents, NVIDIA AI-Q combines world-class retrieval with quick multimodal extraction.
The new NVIDIA AgentIQ toolbox, which enables smooth, heterogeneous communication between agents, tools, and data, powers the blueprint. AgentIQ is an open-source software library that was made available on GitHub today. It is used to build multi-agent, end-to-end systems by integrating, profiling, and optimizing groups of AI agents powered by enterprise data. With a straightforward, 100% opt-in onboarding process, it can be seamlessly integrated in segments or as a whole with current multi-agent systems.
With comprehensive system traceability and profiling, the AgentIQ toolkit also improves transparency by allowing organizations to track performance, spot inefficiencies, and obtain a detailed understanding of the process used to generate business intelligence. The NVIDIA Dynamo open-source library and NVIDIA NIM can be utilized with this profiling data to maximize agentic system performance.
The New Enterprise AI Agent Workforce
IT staff will assist with onboarding and training as AI agents transition into digital workers. By facilitating agent collaboration and maximizing performance across various agentic frameworks, the NVIDIA AI-Q blueprint and AgentIQ toolbox assist digital workers.
Businesses can break down silos, streamline tasks, and reduce response times from days to hours by utilising these tools to connect AI agent teams across solutions such as Salesforce’s Agentforce, Atlassian Rovo in Confluence and Jira, and ServiceNow AI for business transformation.
Additionally, AgentIQ allows developers to work in their favourite environment by integrating with frameworks and technologies such as Letta, CrewAI, LangGraph, Llama Stack, and Microsoft Azure AI Agent Service.
More effective AI agents and the orchestration of multi-agent frameworks utilising the Semantic Kernel which AgentIQ fully supports are made possible by the integration of Azure AI Agent Service with AgentIQ.
Agents and copilots from a variety of businesses are including interactive features and visual perception. Visa, a pioneer in financial services, is automating phishing email analysis at scale by utilising AI agents to improve cybersecurity. Visa can maximize AI’s contribution to effective threat response by optimizing agent performance and costs through the use of AI-Q’s profiler tool.
Start Using AgentIQ and AI-Q
Multimodal agents are now possible because to NVIDIA AI-Q‘s incorporation into the NVIDIA Metropolis VSS design, which combines voice, translation, visual perception, and data analytics for increased intelligence.
Developers can participate in this hackathon and use the AgentIQ toolkit open-source library to gain practical experience in developing agentic systems. Additionally, discover how an NVIDIA solutions architect enhanced AI code generation using the AgentIQ toolkit.
NVIDIA AI-Q built agentic systems need a strong AI data platform. These specialised platforms, which are provided by NVIDIA partners, continuously process data to enable AI agents to reason and answer complicated questions with speed and accuracy.
Get to Know Your Own Research Assistant
This event demonstrates how an AI research agent can synthesize hours of research in minutes when it is fed information from several data sources. With the AI-Q NVIDIA Blueprint, developers can create AI agents that employ reasoning and link to a variety of data sources and tools to accurately and efficiently extract detailed source materials. Large data sets can be summarized by agents using NVIDIA AI-Q, which also produces tokens five times faster and ingests petabyte-scale data fifteen times faster with improved semantic accuracy.
NVIDIA AI-Q Important Features
Sophisticated semantic query
- 15 times quicker business data input using multimodal PDF data extraction and retrieval
- Using NVIDIA NeMo Retriever
- Three times the retrieval latency
- Cross-lingual and multilingual
- Reranking to increase accuracy even more
- GPU-accelerated search and index construction
- Lama Nemotron’s fast reasoning capabilities provide the best accuracy and minimal latency for examining datasets, spotting trends, and coming up with solutions
