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Alibaba Cloud Travel and Hospitality Singapore

Atlas

Application Refactoring · Real-time Analytics · Risk Management

Atlas serves customers through API calls via their proprietary Air Travel Retailing and Information Platform (ATRIP), which aggregates real-time flight information, and provides booking management and payment services. Travelers often run into issues and disappointments when booking flights via online travel agencies. Due to the complicated booking flow invisible to an end consumer, fares often change right before they secure a booking, leading to poor customer experience and low conversions.

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Coupled with the fact that their API is called up to 800 million times each day, Atlas also required a powerful and robust solution that can handle and respond to the immense volume of requests.

Reported impact

Business outcome

All-in-all, leveraging Alibaba Cloud’s solutions have supported Atlas save up to 45% in cloud operating costs when measured against comparable offerings with other cloud service providers.

  • Cost Reduction

Solution

Atlas used Alibaba Cloud to address Atlas serves customers through API calls via their proprietary Air Travel Retailing and Information Platform (ATRIP), which aggregates real-time flight information, and provides booking management and payment services. Travelers often run into issues and disappointments when booking flights via online travel agencies. Due to the complicated booking flow invisible to an end consumer, fares often change right before they secure a booking, leading to poor customer experience and low conversions. Atlas is an innovative travel technology startup based in Singapore, founded by serial entrepreneur Mary Li in 2019. Leveraging decades of experience in travel, aviation, e-commerce and technology, Atlas is harnessing the power of data to reimagine the troublesome booking paths and information flow challenges in the airline distribution industry.

Data flow

Atlas's workloads and source data persist to ApsaraDB for Redis and are delivered through Server Load Balancer with security and operations controls from Application Real-Time Monitoring Service (ARMS).

Solution architecture

5 components · 4 layers
  1. Storage
    • ApsaraDB for Redis In response to Atlas' scalability challenges, the core system was built on top of Alibaba Cloud's Container Service for Container Service for Kubernetes , providing a fully
  2. Serving
    • Server Load Balancer Leveraging Alibaba Cloud's Server Load Balancer and Application Real-Time Monitoring Service , Atlas built a solution to distribute traffic, eliminate single-point-of-failures,
  3. Governance
    • Application Real-Time Monitoring Service (ARMS) Leveraging Alibaba Cloud's Server Load Balancer and Application Real-Time Monitoring Service , Atlas built a solution to distribute traffic, eliminate single-point-of-failures,
  4. Uncategorized
    • Platform for AI At the core of it all, Atlas has built their data analytics and platform on Alibaba Cloud's Platform for AI to handle real-time machine learning of flight searches, prices and
    • Object Storage Service (OSS) In response to Atlas' scalability challenges, the core system was built on top of Alibaba Cloud's Container Service for Container Service for Kubernetes , providing a fully

Architecture clues

  • Primary customer region: Singapore

Evidence from the source

Atlas is solving it by leveraging machine learning and efficient cloud computing infrastructure and achieving 97% fare accuracy rate throughout the booking process.
Atlas serves customers through API calls via their proprietary Air Travel Retailing and Information Platform (ATRIP), which aggregates real-time flight information, and provides booking management and payment services.
Due to the complicated booking flow invisible to an end consumer, fares often change right before they secure a booking, leading to poor customer experience and low conversions.
Furthermore, the nature of Atlas' business sees them handling vast amounts of data that will only continue to grow, giving rise to challenges in the scalability, security, compliance, and cost of their data storage solutions.
Travelers often run into issues and disappointments when booking flights via online travel agencies.
Transparency Evidence & methodology 85/100 reference value · 79% 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 value85/100
  • 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 specificity20/20
    Measures whether the reported benefit is concrete rather than a generic claim.
  • Quantified impact15/25
    1 metric describe measurable impact.
  • Deployment scale10/10
    Rewards evidence of a live or scaled deployment and meaningful integration scope.
Evidence confidence79%
  • 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 provenance0/10
    The publication date has no documented provenance.
  • Source transparency8/10
    1 source reference document publisher, URL, authority, retrieval, and supported fields.
  • Implementation specificity10/10
    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. Alibaba Cloud

    Atlas customer story

    First-party
    https://www.alibabacloud.com/customers/atlas
    Source type
    Vendor-published customer story
    Supports
    • Customer
    • Business problem
    • Solution
    • Products
    • Solution components
    • Data flow
    • Integrations
    • technical area
    • use case category
    • Business outcome
    • outcome category
    • Metrics
    • Architecture
    • evidence quotes

Date evidence

  • First archived Oct 24, 2025 · Internet Archive · Independent First Wayback Machine capture; confirms the page existed by this date, not when it was published.
    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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