Manually formatting order tables consumed full workdays. AI now handles the drafting, freeing staff to tackle previously abandoned goals.
A Japanese construction and renovation company managing diverse operations from exterior wall painting to eco-related projects without dedicated internal IT personnel.
The company wanted to establish internal operational guidelines but lacked the technical expertise to build and maintain a custom corporate portal....
“AIを使う範囲は『うちの会社でできることはこのくらいだろう』というように範囲を勝手に決まってしまっているように思います。AIを活用することで何ができるか分かれば、業務の効率化以外に、今までできなかったことやあきらめていたことにもチャレンジできるようになる。単にツールとして導入するのではなく、未来に向かって動いていく力につなげていきたいというのが今回のAI導入の大きな展望です。”
Shinei Group's Workflow automation is part of this use case:
Manufacturer and distributor of cosmetics, oral care, and personal care products.
Provided the JAPAN AI platform and JAPAN AI SPEECH tool to automate manual creation, report generation, and meeting transcription.
Related implementations across industries and use cases
Building 1,500 seasonal product pages relied on manual image matching. Now, AI pairs assets to assemble layouts and generate social ads.
Evaluating one investment took 2 hours. Custom GPTs cut reviews to 5 minutes, reducing the division's workload by 70%.
Adopting new languages inflated project costs. Now, developers use AI trained on internal code to write and debug unfamiliar languages.
Evaluating one investment took 2 hours. Custom GPTs cut reviews to 5 minutes, reducing the division's workload by 70%.
Japan's shrinking workforce capped headcount. Instead of relying on IT, non-coding staff built AI workflows for daily budget approvals.
Routine queries burdened HR. Now, an AI WhatsApp agent instantly answers remote factory workers, escalating complex issues to HR.
Disparate tools slowed 320,000 employees. Unifying on Teams and Copilot connected the workforce and embedded AI into daily habits.
Manual maintenance reports and routine purchases bottlenecked staff. AI agents now accurately classify faults and recommend suppliers.
QA teams manually searched vast incident logs to assess deviations. Now, multi-agent AI synthesizes past cases into verified summaries.
Manually formatting order tables consumed full workdays. AI now handles the drafting, freeing staff to tackle previously abandoned goals.
A Japanese construction and renovation company managing diverse operations from exterior wall painting to eco-related projects without dedicated internal IT personnel.
The company wanted to establish internal operational guidelines but lacked the technical expertise to build and maintain a custom corporate portal....
“AIを使う範囲は『うちの会社でできることはこのくらいだろう』というように範囲を勝手に決まってしまっているように思います。AIを活用することで何ができるか分かれば、業務の効率化以外に、今までできなかったことやあきらめていたことにもチャレンジできるようになる。単にツールとして導入するのではなく、未来に向かって動いていく力につなげていきたいというのが今回のAI導入の大きな展望です。”
Shinei Group's Workflow automation is part of this use case:
Manufacturer and distributor of cosmetics, oral care, and personal care products.
Provided the JAPAN AI platform and JAPAN AI SPEECH tool to automate manual creation, report generation, and meeting transcription.
Related implementations across industries and use cases
Building 1,500 seasonal product pages relied on manual image matching. Now, AI pairs assets to assemble layouts and generate social ads.
Evaluating one investment took 2 hours. Custom GPTs cut reviews to 5 minutes, reducing the division's workload by 70%.
Adopting new languages inflated project costs. Now, developers use AI trained on internal code to write and debug unfamiliar languages.
Evaluating one investment took 2 hours. Custom GPTs cut reviews to 5 minutes, reducing the division's workload by 70%.
Japan's shrinking workforce capped headcount. Instead of relying on IT, non-coding staff built AI workflows for daily budget approvals.
Routine queries burdened HR. Now, an AI WhatsApp agent instantly answers remote factory workers, escalating complex issues to HR.
Disparate tools slowed 320,000 employees. Unifying on Teams and Copilot connected the workforce and embedded AI into daily habits.
Manual maintenance reports and routine purchases bottlenecked staff. AI agents now accurately classify faults and recommend suppliers.
QA teams manually searched vast incident logs to assess deviations. Now, multi-agent AI synthesizes past cases into verified summaries.