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Microsoft Media and Entertainment United Arab Emirates

Miral

Customer Service Automation

Miral wanted a better way to answer the large volume of visitor questions about Yas Island experiences because traditional bots often failed to satisfy customer needs.

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In just two months, the new Majd AI ambassador built with Azure OpenAI Service was ready to greet the visitors.
The transfer to agents dropped by 3% in about two months, which means our call center is freed up to handle the unique queries that require human interaction.
Who better to guide them than the Majd Al ambassador—an AI concierge available 24/7, powered by Azure OpenAI Service?
Within the first week of launch, our AI chatbot successfully completed over 1,700 operations.

Reported impact

Business outcome

Within the first week of launch, Miral’s AI chatbot completed more than 1,700 operations, and within about two months transfers to human agents dropped by 3%, helping the call center focus on unique queries.

  • Customer Experience
  • Productivity Improvement
  • Speed to Market

Solution

Miral used Microsoft Azure to extend its Noor Analytics initiative into a generative AI concierge for Yas Island visitors. The company built the Majd AI ambassador on Azure OpenAI Service so guests can describe preferences, family needs, and trip goals in natural language and receive personalized recommendations for attractions, dining, shopping, and timing. Because the public website lets anyone ask any question, Miral worked through prompt engineering, architecture reviews, and guardrails to reduce the risk of inappropriate responses and reputational damage. The concierge went from proof of concept to production in two months, runs continuously as a 24/7 digital guide, and escalates complex requests to human agents when needed.

Solution architecture

3 components · 2 layers
  1. Compute
    • Azure OpenAI Service Powers the Majd AI concierge that answers visitor questions and generates personalized recommendations.
    • Azure Provides the secure cloud foundation for Miral’s data-driven and generative AI workloads.
  2. Serving
    • Azure AI Search Supports retrieval of relevant destination and attraction information for the concierge experience.

Architecture clues

  • Miral emphasized prompt-engineering workshops and guardrails to prevent inappropriate responses on a public web channel.
  • Miral used Microsoft Azure and Cognitive Services as part of its Noor Analytics data initiative.
  • The Majd AI ambassador is a 24/7 concierge built on Azure OpenAI Service for the Yas Island website.
  • The chatbot can transfer visitors to a human agent when necessary.

Evidence from the source

Given that the Yas Island website is an open platform where anyone can ask any question, we needed to ensure that it was not possible for someone to manipulate the system into providing inappropriate responses, thus causing reputational damage.
The transfer to agents dropped by 3% in about two months, which means our call center is freed up to handle the unique queries that require human interaction.
Traditional bots often fail to satisfy or address customer needs.
Who better to guide them than the Majd Al ambassador—an AI concierge available 24/7, powered by Azure OpenAI Service?
Within the first week of launch, our AI chatbot successfully completed over 1,700 operations.
Transparency Evidence & methodology 90/100 reference value · 87% 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 value90/100
  • 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 impact25/25
    2 metrics describe measurable impact.
  • Deployment scale10/10
    Rewards evidence of a live or scaled deployment and meaningful integration scope.
Evidence confidence87%
  • 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
    5 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 specificity8/10
    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

    Miral customer story

    First-party
    https://www.microsoft.com/en/customers/story/1752311260413528820-miral-azure-open-ai-service-other-unsegmented-en-united-arab-emirates
    Source type
    Vendor-published customer story
    Published
    Mar 29, 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 Mar 29, 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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