NVIDIA NeMo
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NVIDIA NeMo is a modular software suite of APIs and libraries that help developers manage the AI agent lifecycle—building, deploying, and optimizing AI agents at scale.

NeMo Microservices
Easy-to-use containerized APIs for data preparation, model customization, evaluation, guardrailing, and continuously optimizing AI agents.
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NeMo Framework
Flexible open-source framework for end to end training and development of generative AI models, scaling seamlessly from a single GPU to multi-node clusters.
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NeMo Agent Toolkit
Open-source toolkit for evaluation-based development and optimization of an agentic system.
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Easy-to-use containerized APIs for data preparation, model customization, evaluation, guardrailing, and continuously optimizing AI agents.

NVIDIA NeMo Microservices

A modular collection of containerized services exposed via intuitive APIs that enables developers to seamlessly integrate NeMo into existing platforms.

NeMo Data Designer (EA)
Build high-quality, use-case-specific datasets with fast previews, built-in evaluations, and scalable workflows
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NeMo Customizer
Fine-tune language models with your proprietary data to build domain-specific AI agents.
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NeMo Evaluator
Benchmark and monitor model and agent effectiveness with standard and custom metrics, including LLM-as-a-judge.
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NeMo Retriever
High-accuracy retrieval augmented generation (RAG) pipelines with open-source models and privacy-preserving data access.
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NeMo Guardrails
Add safety, policy, and topical control to model responses.
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Develop multimodal generative AI models with the open-source NeMo Framework.

NVIDIA NeMo Framework

A modular open-source Python framework for large-scale pretraining, post-training, and reinforcement learning of multimodal generative AI models.

NeMo Curator
Clean, filter, and prepare multimodal data with a GPU-accelerated Python library.
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NeMo RL
Align models with a scalable post-training library that integrates Hugging Face and Megatron optimizations.
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NeMo Evaluator
Evaluate model performance with streamlined deployment, benchmark support, and advanced harnesses.
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NeMo AutoModel
Train natively with accelerated PyTorch and finetune Hugging Face models on Day-0.
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NeMo Megatron-Bridge
Train and fine-tune large models using a Megatron-Core parallelism with PyTorch-native training loop.
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NeMo Guardrails
Add programmable safety, control, and compliance to LLM and agentic systems.
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NeMo Run
Configure, execute, and track training or evaluation jobs across local, on-prem, and cloud clusters.
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NeMo Export and Deploy
Export and deploy models to production using TensorRT, TensorRT-LLM, vLLM engines, and Triton backends.
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NeMo VFM
Develop vision foundation models with a PyTorch-native training loop powered by both Megatron-Core and PyTorch backends.
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NeMo Skills
Extend LLM capabilities with reference pipelines for synthetic data generation, training, and benchmark evaluation.
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NeMo Speech
Train and deploy speech AI models, including ASR and TTS, with export support to NVIDIA Riva.
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Monitor and optimize the performance of AI agents and multi-agent systems.

NeMo Agent Toolkit
Build, profile, evaluate, and optimize agentic systems with open-source, framework-agnostic observability toolkit.
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Reference workflows with code, models, and deployment guides that helps developers quickly build and scale AI solutions.

AI-Q Deep Researcher
Build a custom deep researcher powered by state-of-the art models that continuously process and synthesize multimodal enterprise data, enabling reasoning, planning, and refinement to generate comprehensive reports.
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Data Flywheel
Build a data flywheel, to continuously optimize AI agents for latency, cost, and accuracy using automated data curation, evaluation, and fine-tuning with NeMo microservices.
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RAG
Continuously extract, embed, and index multimodal data for fast, accurate semantic search using NeMo Retriever models.
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Deploy and manage AI workloads as scalable, performance-optimized services to seamlessly power enterprise-grade AI agents in production.

NVIDIA NIM
Containerized microservices for secure, performant and reliable deployment of AI models anywhere.
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NVIDIA NIM Operator
Kubernetes-native operator for automating deployment, scaling, and lifecycle management of NIM and NeMo microservices.
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NVIDIA AI Factory
Reference architectures standardizing hardware, networking, and software to build scalable, secure, and high-performance AI infrastructure for production set ups.
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