Google Cloud Software / SaaS Singapore

UIB

Sales Automation

UIB needed a scalable, low-latency, and localized platform for conversational commerce so clients like Transnasional could own customer data, meet Malaysian data residency requirements, and move ticket sales off third-party agents.

Converted more than 60% of ticket sales to WhatsApp
The company now owns and retains 100% of its customer data
WhatsApp now accounts for more than 60% of Transnasional's total ticket sales

Reported impact

Business outcome

The platform helped Transnasional move more than 60% of ticket sales to WhatsApp, retain 100% of its customer data, and replace OTA dependency with a direct conversational sales channel.

  • Customer Experience
  • Revenue Growth
  • Scalability

Solution

UIB built a WhatsApp-based conversational commerce platform on Google Cloud for clients that need direct digital sales channels. The system runs on Google Kubernetes Engine (GKE), which automatically scales with chatbot demand without requiring extra hardware, giving the company a reliable base for revenue-generating customer conversations. UIB added Gemini and Gemma to provide the natural-language layer for the ticketing experience, while Cloud Storage near Malaysia keeps customer information in a company-controlled environment that satisfies localization and latency requirements. In production, this architecture integrates with Transnasional's public transportation ticketing workflow so passengers can discover, book, and complete transactions through WhatsApp instead of external online travel agents. The result is a governed conversational commerce stack that combines messaging, AI, and localized storage on one cloud platform.

Data flow

Passengers start on WhatsApp, where the UIB platform running on GKE handles traffic spikes, routes conversational requests through Gemini and Gemma for language understanding, and stores customer data in Cloud Storage located near Malaysia so Transnasional can complete ticket sales while keeping the data in its own environment.

Solution architecture

4 components · 2 layers
  1. Compute
    • Google Kubernetes Engine (GKE) Hosts the conversational commerce platform and automatically scales with chatbot traffic.
    • Gemini Powers the natural-language capabilities in the conversational ticketing interface.
    • Gemma Supports the natural-language experience used in the conversational interface.
  2. Storage
    • Cloud Storage Stores customer data near Malaysia to meet data residency and low-latency requirements.

Architecture clues

  • GKE is used because traffic is spiky and scales automatically without new hardware.
  • Localized cloud storage was used to satisfy strict Malaysian data residency requirements.
  • The platform was built as the first WhatsApp-based public transportation ticketing solution in Malaysia.
  • UIB consolidated onto one Google Cloud stack before focusing on client-facing solutions.

Evidence from the source

Beyond processing, UIB also uses Gemini and Gemma to power the interface’s natural language capabilities.
Converted more than 60% of ticket sales to WhatsApp
The company now owns and retains 100% of its customer data, and WhatsApp now accounts for more than 60% of Transnasional's total ticket sales.
The custom platform relies on Google Kubernetes Engine (GKE), which can scale up or down automatically to handle chatbot traffic changes without needing to provision additional hardware.
Together, UIB and Transnasional launched the first WhatsApp-based public transportation ticketing solution in Malaysia.
Transparency Evidence & methodology 100/100 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 value100/100
  • Problem clarity20/20
    Measures whether the customer's operational problem is specific enough to compare.
  • Implementation depth25/25
    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
    3 metrics 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. Google Cloud

    UIB customer story

    First-party
    https://cloud.google.com/customers/uibai
    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

  • Sitemap last modified Aug 26, 2026 · Google Cloud · Publisher metadata Publisher-reported modification timestamp; not a publication date.
    Open date source
  • Unverified extracted date Aug 26, 2026 · Google Cloud · Unknown Legacy extracted date without source-page confirmation.
    Open date source
Not separately sourced Industry, Region, Company size. Treat these normalized attributes as lower-confidence until a dedicated source is added.