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Microsoft Telecommunications Indonesia

Telkomsel

Customer Service Automation · Enterprise Knowledge Search · Security and Compliance

Telkomsel, one of the largest digital telco companies in Asia, faced a "good problem to have": burgeoning sales of its products and services.

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Nearly 279 million people live on over 17,000 islands
Nearly 279 million people live on over 17,000 islands and speak more than 700 languages.
Solving the puzzle of perfect support The diversity of Telkomsel's more than 159 million mobile subscribers
Solving the puzzle of perfect support The diversity of Telkomsel's more than 159 million mobile subscribers and its 8.5 million fixed broadband customers is...

Reported impact

Business outcome

The company created its now overwhelmingly popular "Veronika" virtual assistant with Microsoft Azure OpenAI.

  • Customer Experience
  • Revenue Growth
  • Scalability
  • Speed to Market

Solution

Telkomsel used Azure OpenAI Service, Azure AI Speech, Power Platform to replace disconnected manual workflows with a more consistent digital operating model. Low-code automation and copilot capabilities orchestrate tasks, route work, and surface context to agents or business users without requiring separate point solutions. Where generative AI is involved, Azure OpenAI handles the language understanding layer while connected data and workflow services keep responses grounded in enterprise context. The company created its now overwhelmingly popular "Veronika" virtual assistant with Microsoft Azure OpenAI.

Data flow

Content and operational context are prepared in the application data layer, passed to Azure OpenAI for generation or extraction, stored in Azure storage services, and returned through the user-facing application to employees or customers with grounded responses.

Solution architecture

4 components · 2 layers
  1. Compute
    • Azure OpenAI Service Runs large language model inference for summarization, extraction, conversational AI, and grounded answers.
    • Azure AI Speech Handles speech recognition and speech synthesis for voice-driven experiences.
    • Azure Machine Learning Supports model development, experimentation, and deployment for predictive workloads.
  2. Orchestration
    • Power Platform Provides the low-code automation and application platform for workflow modernization.

Architecture clues

  • Uses Azure OpenAI for grounded generation or large-scale extraction workloads.

Evidence from the source

"Azure OpenAI Service provided the intelligence that delivers accurate, personalized results for our customers," he emphasizes.
"With the ChatGPT model accessed through Azure OpenAI Service, we're using the best AI technology now available," says Danang Andrianto, Vice President of Customer Journey and Digital Experience at Telkomsel.
So when Microsoft introduced Azure OpenAI Service , Telkomsel was ready with a blueprint for its ideal virtual assistant.
Telkomsel, one of the largest digital telco companies in Asia, faced a "good problem to have": burgeoning sales of its products and services.
The company created its now overwhelmingly popular "Veronika" virtual assistant with Microsoft Azure OpenAI.
Transparency Evidence & methodology 66/100 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 value66/100
  • 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 specificity16/20
    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 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

    Telkomsel customer story

    First-party
    https://www.microsoft.com/en/customers/story/1739790055278570755-telkomsel-azure-openai-service-telecommunications-en-indonesia
    Source type
    Vendor-published customer story
    Published
    Feb 23, 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 23, 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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