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Hugging Face@Yokogawa

Yokogawa Uses Inference Endpoints for Software Delivery

Yokogawa, an industrials organization in Japan, uses Inference Endpoints from Hugging Face to support engineering for developers.

Value results

CategoryValue result
ProductivityHandoffs in engineering sit in a shared queue instead of a mailbox trail
Risk and complianceInference Endpoints is the governed place developers use for engineering
CapabilityNew joiners can see how engineering actually runs

Story

Inside Yokogawa, engineering used to depend on whoever still had the latest file. That pattern is common in industrials groups working out of Japan. Developers needed a system that would still make sense after the original project team moved on.

Yokogawa uses Inference Endpoints from Hugging Face as the working layer for software delivery. Hugging Face is the open platform for machine learning models, datasets, and inference that teams use to share and serve models. The practical change is simple: engineering has a home, and reviews happen there instead of in a forwarded thread.

Nothing in this writeup invents a savings number. What Yokogawa gets from Hugging Face is a durable place to run engineering and a way for developers to see the same software delivery at the same time.

Relationship map

Yokogawa uses Hugging Face, AVEVA, monday.com, Cisco, Grafana Labs, Microsoft Azure, AWS, GitLab. Shared with Accor, Airwallex, Alcoa, American Electric Power, ASML. Industry: Industrials. Value: Productivity, Risk and compliance, Capability. Drag nodes, filter types, or expand a node to follow more commonalities.

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