Nvidia Makes NeMo Microservices Generally Available to Accelerate Development of Autonomous AI Agents

Nvidia has announced the general availability of its NeMo microservices, a suite of tools aimed at helping developers build and deploy AI agents quickly and effectively.

To operate efficiently, agents require reliable, real-time, and often proprietary data. Without this, their responses can become less accurate over time.

To address this, Nvidia's NeMo microservices offer tools like Customizer, Evaluator, Guardrails, Retriever, and Curator.

These tools simplify everything from fine-tuning language models to enforcing behavioral rules, evaluating performance, and retrieving enterprise data.

For example, Customizer accelerates model training by up to 1.8 times, while Guardrails ensures safe, compliant agent behavior with minimal latency impact.

NeMo microservices are compatible with various infrastructures, including cloud and on-prem systems, and support models such as Meta’s Llama and Google’s Gemma.

By offering easy API access and support for major AI frameworks like LangChain and LlamaIndex, Nvidia is enabling businesses to develop sophisticated multi-agent systems, bringing AI-driven collaboration closer to reality.

"NVIDIA NeMo™ is an end-to-end platform for developing custom generative AI—including large language models (LLMs), vision language models (VLMs), retrieval models, video models,  and speech AI—anywhere. 

"With NeMo, you can easily build data flywheels to continuously optimize AI agents with the latest information. NeMo accelerates the data flywheel by curating AI and human feedback, refining and evaluating models, and deploying with guardrails and retrieval-augmented generation (RAG) to keep agents delivering peak performance," Nvidia said in a blog post.