Editor’s note: This post is part of the Nemotron Labs blog series, which explores how the latest open models, datasets and training techniques help businesses build specialized AI systems and applications on NVIDIA platforms. Each post highlights practical ways to use an open stack to deliver real value in production — from transparent research copilots to scalable AI agents.
Companies are asking how to build specialized AI that fits with the way their workflows actually run.
The first wave of enterprise AI was about access. Companies experimented with new frontier and open models, ran pilots and explored how AI can help.
Now, specialized agents — systems of models that can reason, use tools and take action even for the most complex workflows — put more useful AI within reach of the people who already know the work best.
Agents are already helping life sciences researchers accelerate medicine discovery, security teams investigate vulnerabilities with more context and operations teams seamlessly coordinate supply chains.
To tap into these specialized agents, businesses are using a foundation they can adapt and own: one built on models they can customize, tools that connect to systems they already use and infrastructure that lets agents operate safely at scale.
NVIDIA Agent Toolkit — comprising models, tools, skills and a secure runtime — provides an open, modular foundation for building safer, faster, lower-cost digital AI coworkers that enterprises and developers can customize, specialize, control and trust.
Enterprises and developers building secure, specialized AI agents require:
Key considerations
- Investor positioning can change fast
- Volatility remains possible near catalysts
- Macro rates and liquidity can dominate flows
Reference reading
- https://blogs.nvidia.com/blog/nvidia-agent-toolkit-open-models-tools-skills-secure-runtime-ai-agents/#primary
- https://blogs.nvidia.com/blog/author/justin-boitano/
- https://blogs.nvidia.com/blog/nvidia-agent-toolkit-open-models-tools-skills-secure-runtime-ai-agents/#disqus_thread
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- How Jaiveer Singh Is Helping Robots — and Developers — Move Faster
- NVIDIA Vera CPU Opens the Way for Agentic Scientific AI at Los Alamos National Laboratory
- RAM crisis provokes enthusiast to try Windows 11 on DDR1-era hardware — other key vintage components included the Core 2 Q6600 and ATI Radeon HD 4650 AGP
- NVIDIA and AWS Collaborate to Bring AI to Production at Scale
Informational only. No financial advice. Do your own research.