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Manufacturing & Industrial

AI for industrial groups.

One privately deployed platform across every business unit automotive to energy that connects to the systems each already runs, backed by local on-site engineers.

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Deployed in Production at.

A Fortune 500 industrial technology group

The local operations of a Fortune 500 industrial technology group run a privately deployed Dify Enterprise as their centralized AI platform, covering four business areas.

The platform integrates with the group's existing internal systems through plugins and SDK, supported by a local engineering team: five-day, eight-hour daily coverage with a one-hour on-site response SLA for production-critical issues.

More than 300 cross-department users now build and run AI applications on the same private platform — well past the pilot stage and into everyday operations.

Read the full storyHow a Fortune 500 Industrial Group Runs Its Private AI Platform on Dify Enterprise
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  • 4

    Business areas on one private Dify platform

  • 300+

    Cross-department users in production, past pilot

  • 20+

    Internal OA, knowledge and workflow systems integrated via plugins & SDK

  • 1h

    Local on-site SLA for production-critical issues

Source: Dify Enterprise deployment at a Fortune 500 industrial technology group | Industry data: MarketsandMarkets, Design News, Google Cloud (2025–2026)

Why
this industry, why now.

The constraints

Industrial groups are adopting AI across their operations, but the practical constraints are consistent. Each business unit runs on different systems, different processes and different data sources. Nobody wants to rebuild what already works.

Country operations of multinationals expect enterprise software supported locally, with fast response times for production-critical issues.

And AI that sits outside the corporate network is not an option for most industrial use cases involving proprietary product data, manufacturing processes or customer specifications.

The role of AI

For this industry, the question is not whether to adopt AI. It is whether one private environment can carry all the business units, connect to the existing IT estate, and be supported locally without requiring a separate platform per business area.

Patterns we see.

One private platform, many business units
Rather than each business unit standing up its own AI environment, industrial groups consolidate onto a single privately deployed Dify Enterprise instance. Each unit gets its own workspace. Governance, models and infrastructure sit at the platform level. Application logic sits with the teams that understand their own workflows.
Integrate, don't rip and replace
An industrial group already runs working OA systems, internal knowledge bases and workflow tools. Dify connects to these through plugins and the SDK rather than replacing them. Existing IT investments stay in place. Dify adds the orchestration layer that lets those systems participate in AI workflows.
Local delivery with on-site SLA
Country operations of multinationals expect enterprise software supported locally, with response times matched to production requirements. The deployment runs inside the local infrastructure. Support is delivered on site, with SLAs suited to production-critical environments rather than global helpdesk schedules.

Discuss Manufacturing & Industrial Technology workflows with Dify.

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