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Microsoft Software / SaaS Japan

MHI

Application Refactoring

Since its establishment in 1884, Mitsubishi Heavy Industries, Ltd. (MHI) has been providing a wide range of products and services in various fields - including energy, engineering, defense and space, and mechanical systems, as a "comprehensive infrastructure company that supports peoples' lives through engineering and manufacturing". Among these is the field known as the "Energy Domain," where the company's gas turbines, boilers, and other power generation equipment, as well as operation and maintenance solutions, support the large-scale power generation facilities that are indispensable to our daily lives.

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Reported impact

Business outcome

MHI has declared its intention to become carbon neutral by 2040.

  • Cost Reduction
  • Customer Experience
  • Productivity Improvement
  • Scalability

Solution

MHI built its Microsoft solution to improve application modernization workflows. Since its establishment in 1884, Mitsubishi Heavy Industries, Ltd. (MHI) has been providing a wide range of products and services in various fields - including energy, engineering, defense and space, and mechanical systems, as a "comprehensive infrastructure company that supports peoples' lives through engineering and manufacturing". Among these is the field known as the "Energy Domain," where the company's gas turbines, boilers, and other power generation equipment, as well as operation and maintenance solutions, support the large-scale power generation facilities that are indispensable to our daily lives. Key components included Azure OpenAI Service ran model inference or heavy processing, and Azure AI Studio coordinated workflows, prompts, or deployment.

Data flow

User prompts and domain content are orchestrated through Azure AI Studio, processed by Azure OpenAI Service, and then delivered through Azure OpenAI Service so MHI can return context-aware answers or automation in the flow of work.

Solution architecture

3 components · 3 layers
  1. Compute
    • Azure OpenAI Service Runs large language models that generate grounded responses, summaries, and copilots.
  2. Serving
    • Azure AI Search Indexes enterprise content so copilots and applications can retrieve grounded answers.
  3. Orchestration
    • Azure AI Studio Provides the build environment for prompt orchestration, safety controls, and model tuning.

Architecture clues

  • "We evaluated Microsoft's API, 'Azure OpenAI Service on your data,' but it didn't seem to give us the results we wanted.

Evidence from the source

"We evaluated Microsoft's API, 'Azure OpenAI Service on your data,' but it didn't seem to give us the results we wanted.
Azure OpenAI Service would first create an answer to the question from the trained data.
For generic questions, Azure OpenAI Service may be able to find the answer in that trained data.
MHI has declared its intention to become carbon neutral by 2040.
Since MHI was an early adopter of Microsoft's Azure OpenAI Service - which ensures that customer data is not used for training of generative AI - there was no concern that the input information for the generative AI would be leaked outside the company.
Since its establishment in 1884, Mitsubishi Heavy Industries, Ltd. (MHI) has been providing a wide range of products and services in various fields - including energy, engineering, defense and space, and mechanical systems, as a "comprehensive infrastructure company that supports peoples' lives through engineering and manufacturing". Among these is the field known as the "Energy Domain," where the company's gas turbines, boilers, and other power generation equipment, as well as operation and maintenance solutions, support the large-scale power generation facilities that are indispensable to our daily lives.
Transparency Evidence & methodology 62/100 reference value · 85% confidence · 1 source

Review how this reference was scored and trace each normalized claim back to its documented source.

01

Scoring methodology

How scores are calculated

Customer Reference Value measures usefulness as a customer reference. Evidence Confidence measures the quality and traceability of available evidence, not independent verification.

Customer reference value62/100
  • Problem clarity20/20
    Measures whether the customer's operational problem is specific enough to compare.
  • Implementation depth20/25
    Rewards named components, data flow, integrations, and architecture detail.
  • Outcome specificity12/20
    Measures whether the reported benefit is concrete rather than a generic claim.
  • Quantified impact0/25
    0 metrics describe measurable impact.
  • Deployment scale10/10
    Rewards evidence of a live or scaled deployment and meaningful integration scope.
Evidence confidence85%
  • Source authority20/25
    The main evidence is an official vendor-published customer story.
  • Claim traceability21/25
    10 of 12 key fields link to a named source.
  • Direct evidence20/20
    6 direct source quotes retained.
  • Date provenance10/10
    The publication date comes from the source page or publisher.
  • Source transparency8/10
    1 source reference document publisher, URL, authority, retrieval, and supported fields.
  • Implementation specificity6/10
    Rewards source-backed components, data flow, quantified impact, and a specific outcome.
02

Traceability

Sources & provenance

Field coverage shows which facts each source supports. Dates are shown only when documented by the source.

  1. Microsoft

    MHI customer story

    First-party
    https://www.microsoft.com/en/customers/story/1779541850037077027-mhi-azure-discrete-manufacturing-en-japan
    Source type
    Vendor-published customer story
    Published
    Jul 5, 2024
    Supports
    • Customer
    • Business problem
    • Solution
    • Products
    • Solution components
    • Data flow
    • Integrations
    • technical area
    • use case category
    • Business outcome
    • outcome category
    • Metrics
    • Architecture
    • evidence quotes
    • Publication date

Date evidence

  • Published on source page Jul 5, 2024 · Microsoft · First-party
    Open date source
Not separately sourced Industry, Region, Company size. Treat these normalized attributes as lower-confidence until a dedicated source is added.

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