AI BriefingLangChain and NVIDIA Launch NemoClaw Deep Agents Blueprint
Key point
LangChain and NVIDIA have launched the NemoClaw blueprint for building high-performance agents for enterprises.
Details
For enterprises to build high-performance AI agents in production environments, full system control—including tool control, context management, evaluation, and execution environment—is essential beyond just model selection.
LangChain and NVIDIA announced the NemoClaw for LangChain Deep Agents blueprint to help enterprises build open and manageable agent systems. This blueprint combines LangChain Deep Agents Code, NVIDIA Nemotron 3 Ultra, and the NVIDIA OpenShell runtime to provide an optimized agent stack.
The key components are as follows:
- Open Model Layer: Nemotron 3 Ultra, which can be customized and optimized for enterprise workloads.
- Tuned Agent Harness: LangChain Deep Agents Code (dcode), which supports planning, tool use, memory, and task execution.
- Managed Runtime: NVIDIA OpenShell, a secure sandbox environment that controls the agent's tool and data interaction policies.
In performance tests, Nemotron 3 Ultra, when combined with the LangChain Deep Agents harness, recorded a benchmark score of 0.86, demonstrating overwhelming efficiency with approximately 10x lower inference cost ($4.48 vs $43.48) compared to competing models.
This low inference cost enables more frequent evaluations (Evals) throughout the agent development lifecycle, ultimately providing an environment for continuously improving agent quality and stability.
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