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    LangChain shares guide to scaling AI agents across enterprises

    LangChain says the guide draws on lessons from Schneider Electric, Vodafone and monday.com about moving beyond isolated agent experiments.

    LA
    1 Source, 11h ago, first seen 11h ago

    TLDR

    LangChain shared a guide on moving agent experiments toward production AI at enterprise scale. It says the guide covers shared agent platforms and LLMOps, observability and evaluation, multi-agent architectures, security, data residency, and adoption across teams.

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    1 Source

    @LangChainWhat does it take to move from isolated agent experiments to production AI at enterprise scale? Our latest guide brings together lessons from @SchneiderElec, V@odafone, and @mondaydotcom across: - Shared agent platforms and LLMOps - Production observability and evaluation - Multi-agent architectures - Clearer boundaries between agents, tools, and environments - Security, governance, and data residency - Scaling adoption across teams and business units https://info.langchain.com/guide/scaling-agents-in-europe-and-the-middle-east