Microsoft Azure is announcing a significant advancement in their AI development and implementation. The NVIDIA AgentIQ tools and NVIDIA NIM microservices have been integrated into Azure AI Foundry in partnership with NVIDIA, enabling previously unheard-of levels of performance, efficiency, and cost optimisation for your AI applications.
A new era of AI efficiency
More than just creativity is needed to scale AI applications in current fast-paced digital environment; efficient procedures that provide quick time-to-market without sacrificing performance are also necessary. Every efficiency improvement matters since enterprise AI initiatives typically take nine to twelve months to complete from inception to production. By streamlining each stage of the AI development lifecycle, Microsoft Azure’s integration aims to rectify that.
NVIDIA NIM on Azure AI Foundry
NVIDIA NIM, a collection of user-friendly microservices designed for safe, dependable, and high-performance AI inferencing, is a component of the NVIDIA AI Enterprise software suite. Using powerful technologies like PyTorch, TensorRT, TensorRT-LLM, and NVIDIA Triton Inference Server, NIM microservices are designed to scale easily on managed Azure compute.
They offer:
- Zero-configuration deployment: Use unconventional optimisation to get up and running fast.
- Smooth Azure integration: Easily integrates with Semantic Kernel and Azure AI Agent Service.
- Enterprise-grade dependability: Take advantage of NVIDIA AI Enterprise’s support for ongoing security and performance.
- Scalable inference: For demanding applications, leverage Azure’s NVIDIA-accelerated infrastructure.
- Workflows have been optimised to speed up applications ranging from sophisticated analytics to massive language models.
These services are easy to deploy. You can use models such as the Llama-3.3-70B-NIM or others from the Azure AI Foundry model catalogue into your AI workflows and begin developing generative AI apps that function seamlessly within the Azure environment with a few clicks.
Optimizing performance with NVIDIA AgentIQ
NVIDIA AgentIQ takes front stage after your NVIDIA NIM microservices are deployed. With the help of this open-source toolkit, you can easily link, profile, and optimise groups of AI agents, allowing your systems to function at their best. NVIDIA AgentIQ provides:
Profiling and optimization
Reduce latency and CPU overhead by optimising AI agent deployment with real-time telemetry.
Dynamic inference enhancements
Until dynamically enhance agent performance, continuously gather and examine metadata such as expected token lengths, estimated time until next inference, and predicted output tokens per call.
Integration with Semantic Kernel
Your agents are further empowered with improved semantic reasoning and task execution capabilities through direct interaction with Azure AI Foundry Agent Service.
In addition to lowering computation costs, this intelligent profiling improves accuracy and reactivity, ensuring that every aspect of your agentic AI workflow is successful.
Furthermore, the NVIDIA Llama Nemotron Reason open reasoning methodology will soon be integrated. A potent set of AI models for sophisticated reasoning is NVIDIA Llama Nemotron Reason. NVIDIA claims that Nemotron is a master of coding, sophisticated mathematics, and scientific thinking. It also comprehends user intent and calls tools like search and translations with ease to complete tasks.
NVIDIA AgentIQ
An open-source framework called NVIDIA AgentIQ is used to link, assess, and speed up groups of AI agents. The AgentIQ toolbox optimises and improves the accuracy of full-stack, sophisticated agentic AI systems while streamlining development.
How AgentIQ Works
With the help of NVIDIA AgentIQ, developers from all over the company may connect their own intelligent, personalised agents and incorporate them into unique workflows. Utilise the open-source library’s resources to facilitate the creation and assessment of accelerated agentic systems.
Simplify Development
Use AgentIQ’s configuration builder to quickly and simply experiment with and prototype new agentic AI applications. You may link and select the agent frameworks that are most appropriate for each activity in a workflow with flexibility with universal descriptors for agents, tools, and workflows. To make the construction of agentic AI systems easier, access a reusable set of tools, pipelines, and agentic processes.
Access a Collection of Tools
Easily create agentic systems. Create a highly accurate, scalable RAG pipeline, a digital human communication interface, or an AI agent for research and reporting by utilising the best retrieval-augmented generation (RAG) architectures, workflows, and search tools available throughout your company or by utilising NVIDIA AI Blueprints, developed with NVIDIA NIM and NeMo.
Accelerate Agent Responses
Optimise agentic AI processes by utilising fine-grained telemetry. NVIDIA NIM and NVIDIA Dynamo will use this profiling data to maximise agentic system performance. Better business outcomes can be achieved without upgrading the underlying infrastructure by using these predicted metrics, which can include information about an inference call to an LLM for a specific agent, such as what prompt is in memory, where it might reside, and which other agents are likely to call it.
Increase Accuracy
Use metrics gathered using the NVIDIA AgentIQ toolkit to assess the accuracy of an agentic system, then link them to your orchestration and observability tools. Recognise areas for improvement by comprehending and debugging the inputs and outputs for every part of an agentic process. Use the NVIDIA AgentIQ toolset to rapidly reassess the pipeline and determine its impact by changing out tools or models.
