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How Schneider Electric Built Their LLMOps Foundations At Enterprise Scale With LangSmith

Blog post from LangChain

Post Details
Company
Date Published
Author
Yoann Bersihand, Nicolas Gauthier, Amaury Gelin
Word Count
1,978
Company Posts That Month
29
Language
English
Hacker News Points
-
Post removed?
No
Summary

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.

Trends Found in this Post
Trend Post Mentions Total Month Mentions Posts Companies MoM
Observability 8 4,170 814 198 -2%
AI Coding Assistant 4 1,864 516 156 -17%
AI Agents 3 6,829 1,441 261 +10%
LLM 2 7,655 1,347 245 +22%
Real-time 2 6,395 1,450 242 +6%
Developer Experience 1 590 278 93 +37%
Harness engineering 1 262 158 63 +3%
Platform Engineering 1 1,431 351 79 -11%
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