LangChain has collaborated with NVIDIA to introduce the NemoClaw for LangChain Deep Agents blueprint, an open architecture that is meant to assist companies in developing, testing, and deploying advanced AI agents while keeping control of their own intelligence. This blueprint includes the LangChain Deep Agents Code, NVIDIA Nemotron 3 Ultra, and NVIDIA OpenShell, which helps companies customize their AI agents. As enterprises increasingly move AI agents into production, the solution allows them to preserve ownership of critical assets such as agent memory, workflows, traces, model weights and tuning data while continuously improving performance. According to LangChain’s evaluation benchmarks, NVIDIA Nemotron 3 Ultra, when paired with LangChain Deep Agents, achieved an aggregate score of 0.86 at an inference cost of $4.48, delivering comparable performance at approximately one-tenth the cost of the next best-performing model.
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“The way to build better agents is to keep improving the system around the model,” said Harrison Chase, Co-founder and CEO of LangChain. “Memory, tool use, evaluation, and model behavior compound when teams can tune them together. Our work with NVIDIA shows that enterprises can get strong performance from an open stack while keeping control over the agent systems they’re building.” “Super agents have arrived,” said Jensen Huang, Founder and CEO of NVIDIA. “With an open model like NVIDIA Nemotron, a LangChain harness, the NVIDIA OpenShell runtime, and a company’s own data, every enterprise can build custom agents that understand its business, use its tools, and turn knowledge into action. The future of AI won’t be one-size-fits-all – companies will use AI cloud services and build their own AI, shaped by their proprietary data, know-how, and workflows, and run it safely and securely wherever they operate.”