How Schneider Electric Built Their LLMOps Foundations At Enterprise Scale With LangSmith
Blog post from LangChain
Schneider Electric is leveraging artificial intelligence to enhance energy efficiency and sustainability across industries, with a focus on electrification, automation, and digitalization. The company operates an extensive AI program through its AI Hub, which involves 350 experts deploying over 60 AI agents to optimize energy consumption, prolong asset lifespans, and boost developer productivity. Central to their strategy is the use of AI to forecast energy demand and production, enabling users to shift electricity usage to cost-effective, eco-friendly times. Schneider's AI operations are underpinned by a robust LLMOps framework built around the LangSmith and LangChain ecosystems, which supports observability, evaluation, and deployment of AI products. This framework ensures data privacy, compliance, and high-quality agent performance, fostering a collaborative environment where subject matter experts can contribute to the development and refinement of AI solutions. Schneider's AI initiatives, such as the internal AI Assistant "One Jo" and the Customer Success Manager Copilot, demonstrate the company's commitment to integrating AI in critical infrastructure while maintaining rigorous cybersecurity standards. Through these efforts, Schneider is advancing its mission to drive sustainable energy management and industrial automation, with a vision of significantly reducing global energy consumption and carbon emissions.
| Trend | Post Mentions | Total Month Mentions | Posts | Companies | MoM |
|---|---|---|---|---|---|
| Observability | 8 | 1,844 | 344 | 128 | -56% |
| AI Coding Assistant | 4 | 807 | 220 | 102 | -62% |
| AI Agents | 3 | 3,092 | 648 | 191 | -49% |
| LLM | 2 | 3,751 | 612 | 168 | -39% |
| Real-time | 2 | 2,883 | 708 | 173 | -49% |
| Developer Experience | 1 | 271 | 111 | 50 | -33% |
| Harness engineering | 1 | 137 | 67 | 36 | -46% |
| Platform Engineering | 1 | 544 | 153 | 49 | -67% |
Use this post, company, and trend context to find content marketing opportunities, perform competitive analysis, or address product feature gaps via the Plushcap MCP server or the Plushcap API.