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Microsoft Travel and Hospitality Switzerland

Rhatische Bahn AG

Customer Service Automation

Rhaetian Railway (RhB) has a long and illustrious tradition. Not least thanks to the spectacular routes it covers, it commands deep international respect: Customers from around the globe plan their trips on the Bernina and/or Glacier Express months in advance.

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Reported impact

Business outcome

Rhaetian Railway (RhB) has a long and illustrious tradition. Not least thanks to the spectacular routes it covers, it commands deep international respect: Customers from around the globe plan their trips on the Bernina and/or Glacier Express months in advance.

  • Customer Experience
  • Revenue Growth
  • Risk Reduction

Solution

Rhaetian Railway (RhB) has a long and illustrious tradition. Not least thanks to the spectacular routes it covers Rhaetian Railway (RhB) has a long and illustrious tradition. Not least thanks to the spectacular routes it covers, it commands deep international respect: Customers from around the globe plan their trips on the Bernina and/or Glacier Express months in advance. Using artificial intelligence to chart new paths in customer care ParetoLabs developed an initial version of the digital assistant Flurina in several phases. The implementation centers on Azure OpenAI Service, Azure to support customer service automation workflows.

Solution architecture

2 components · 1 layer
  1. Compute
    • Azure OpenAI Service Generates responses and language understanding for the customer-facing or employee-facing assistant.
    • Azure Provides the underlying cloud infrastructure, identity, and managed services for the solution.

Architecture clues

  • ParetoLabs developed an initial version of the digital assistant Flurina in several phases.

Evidence from the source

Recent years have seen a constant rise in the number of customer inquiries coming into RhB's Rail Service unit by phone and in writing. The extra work for staff was then made worse by the general shortage of skilled labor.
Rhaetian Railway (RhB) has a long and illustrious tradition. Not least thanks to the spectacular routes it covers
Transparency Evidence & methodology 56/100 reference value · 75% 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 value56/100
  • 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 specificity16/20
    Measures whether the reported benefit is concrete rather than a generic claim.
  • Quantified impact0/25
    0 metrics describe measurable impact.
  • Deployment scale5/10
    Rewards evidence of a live or scaled deployment and meaningful integration scope.
Evidence confidence75%
  • 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 evidence10/20
    2 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

    Rhatische Bahn AG customer story

    First-party
    https://www.microsoft.com/en/customers/story/1737543866273038641-rhb-azure-openai-service-government-en-switzerland
    Source type
    Vendor-published customer story
    Published
    Feb 27, 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 Feb 27, 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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