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IBM Energy Hong Kong

Towngas

Customer Service Automation

Towngas needed to handle surging customer-support demand, language complexity and longer call waits while reducing the labor intensity of its contact center during the pandemic.

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100% reduction in customer wait times
50% increase in customer self-service
around 15% of calls deflected away from human agents

Reported impact

Business outcome

Towngas eliminated customer waiting for supported scenarios, drove higher self-service adoption and improved the efficiency and continuity of support operations.

  • Cost Reduction
  • Customer Experience
  • Productivity Improvement

Solution

Towngas modernized its contact center with a voice and chatbot assistant built by Mobinology Asia on IBM watsonx Assistant and the partner’s SYVA AI chatbot platform. The goal was to replace phone-tree interactions with conversational AI and create a single, AI-enabled CRM experience for customer-service teams. IBM watsonx Assistant provides the contact-center intelligence for routing and self-service, while SYVA and the surrounding CRM architecture connect voice, call handling and omnichannel support workflows. The implemented Tinny virtual assistant supports interactive voice response, automatic call diversion, better workforce management and real-time analytics, while keeping service available 24x7. By shifting routine interactions into a conversational self-service channel and integrating those interactions back into CRM processes, Towngas reduced dependency on human-only call handling and created a more responsive customer experience.

Data flow

Customer calls and digital requests are routed into the Tinny virtual assistant, where watsonx Assistant handles conversational self-service and the SYVA-powered CRM workflow feeds outcomes back into contact-center operations and analytics.

Solution architecture

2 components · 2 layers
  1. Serving
    • IBM watsonx Assistant Powers the conversational AI and contact-center capabilities behind the Tinny virtual assistant.
  2. Orchestration
    • SYVA AI chatbot platform Provides the partner chatbot framework and CRM orchestration used to implement Tinny.

Architecture clues

  • Designed to provide a single version of the truth for the contact center team
  • Supports interactive voice response and real-time analytics
  • Tinny replaced the previous phone-tree system

Evidence from the source

Mobinology built the chatbot Tinny with IBM watsonx Assistant technology along with its own SYVA AI chatbot platform to architect the CRM for Towngas.
The 24x7 self-service chatbot solution delivered 100% reduction in customer wait times.
The Tinny chatbot effectively replaced the phone-tree system with conversational AI capabilities.
Transparency Evidence & methodology 95/100 reference value · 84% 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 value95/100
  • 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 scale5/10
    Rewards evidence of a live or scaled deployment and meaningful integration scope.
Evidence confidence84%
  • 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 evidence15/20
    3 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 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. IBM

    Towngas customer story

    First-party
    https://www.ibm.com/case-studies/towngas
    Source type
    Vendor-published customer story
    Published
    May 14, 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

Not separately sourced Industry, Region, Company size. Treat these normalized attributes as lower-confidence until a dedicated source is added.

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