Developing an AI-Native Engineering Organization with Claude Code. Money Forward Featured in Anthropic Case Study.

Money Forward Press Announcement: 
https://corp.moneyforward.com/en/news/release/corporate/20260129-mf-press-1/

Anthropic Case Study: 
https://claude.com/customers/money-forward 

Through a back-office SaaS product line-up such as 'Money Forward Cloud,' Money Forward is on its way to maximize AI capabilities by harnessing the outcome of both AI-implemented and AI-native products.  ^*1

Beyond embedding AI in our products, internal AI integration is actively promoted by the Company. We aim to become an AI-native organization where every engineering process is built with AI utilization. ^*2

Being selected as an Anthropic case study allows us to level up our productivity even further. By tapping into Anthropic's elite technical support, we’re sharpening our platform to deliver high-quality, high-speed value to our users.

※1 Money Forward “AI Initiatives” https://corp.moneyforward.com/service/ai/ (Japanese only)

※2 Money Forward “AI Usage Guidelines”: https://corp.moneyforward.com/en/user_data_guide/ai-guidelines/

Core Accomplishments via Claude Code (Selected Data)

1/ Approximately 70% Decrease in API Implementation Man-hours

The duration necessary for deploying new APIs was successfully lowered from a two-day average to just five hours. Because Claude Code was responsible for producing roughly 80% of the functional code, the engineering team could redirect their expertise toward high-level strategic activities, including architectural planning and rigorous code evaluation.

2/ Substantial Optimization of the Onboarding Timeline

By utilizing interactive automation scripts for the configuration of development environments, the time required to onboard new team members was condensed from roughly one full week to only a single day.

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