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Microsoft Manufacturing France

ALSTOM TRANSPORT

Enterprise Knowledge Search

"Industrials are facing existential and structuring challenges: how can they remain competitive, continue to lead the market share, continue to innovate while executing the operational backlog, be agile and adapt to the new and growing market needs

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One concrete example of its capabilities is regarding how AI is supporting engineering teams writing specifications for the development of a railway system to then be able to implement them.

Reported impact

Business outcome

One concrete example of its capabilities is regarding how AI is supporting engineering teams writing specifications for the development of a railway system to then be able to implement them. " A poorly written requirement costs an average of one day's salary " explains Mohamed Habib Mazouni.

  • Cost Reduction
  • Customer Experience
  • Productivity Improvement
  • Scalability
  • Speed to Market

Solution

Alstom, a worldwide leader in the railway sector, operates in more than sixty countries, providing rolling stock, signaling systems, and services for rail. "Industrials are facing existential and structuring challenges: how can they remain competitive, continue to lead the market share, continue to innovate while executing the operational backlog, be agile and adapt to the new and growing market needs "Industrials are facing existential and structuring challenges: how can they remain competitive, continue to lead the market share, continue to innovate while executing the operational backlog, be agile and adapt to the new and growing market needs The railway industry is both specific and fluctuant, creating the needs to develop in-house applications. The implementation centers on Azure OpenAI Service, Azure AI Studio, Microsoft Teams, GitHub Copilot to support enterprise knowledge search workflows.

Solution architecture

4 components · 3 layers
  1. Compute
    • Azure OpenAI Service Powers the generative assistant that helps employees search, summarize, and draft content.
  2. Serving
    • Microsoft Teams Acts as the collaboration surface for prompts, meetings, and shared knowledge.
    • GitHub Copilot Assists developers with code generation and implementation tasks.
  3. Orchestration
    • Azure AI Studio Provides the managed environment for building, evaluating, and governing AI applications.

Architecture clues

  • Alstom, a worldwide leader in the railway sector, operates in more than sixty countries, providing rolling stock, signaling systems, and services for rail.
  • One concrete example of its capabilities is regarding how AI is supporting engineering teams writing specifications for the development of a railway system to then be able to imple...
  • With over a thousand users and more than 15,000 operations conducted each month, Alstom's AI services proves to be successful, grows rapidly and keeps evolving.

Evidence from the source

"Industrials are facing existential and structuring challenges: how can they remain competitive, continue to lead the market share, continue to innovate while executing the operational backlog
Alstom, a worldwide leader in the railway sector, operates in more than sixty countries, providing rolling stock, signaling systems, and services for rail.
One concrete example of its capabilities is regarding how AI is supporting engineering teams writing specifications for the development of a railway system to then be able to implement them.
Transparency Evidence & methodology 65/100 reference value · 80% 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 value65/100
  • Problem clarity20/20
    Measures whether the customer's operational problem is specific enough to compare.
  • Implementation depth15/25
    Rewards named components, data flow, integrations, and architecture detail.
  • Outcome specificity20/20
    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 confidence80%
  • 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 evidence15/20
    3 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

    ALSTOM TRANSPORT customer story

    First-party
    https://www.microsoft.com/en/customers/story/1779144753409953376-alstom-azure-openai-service-travel-and-transportation-en-france
    Source type
    Vendor-published customer story
    Published
    Jun 13, 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 Jun 13, 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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