Hong KongRail + propertyScale · $100K
MTR Corporation

The city that runs on rails — agentic passenger and tenant service for MTR's rail-plus-property estate

MTR is Hong Kong's circulatory system — millions of daily rail journeys plus the malls, offices and housing estates built above the stations — and every fare question, lost-property call, tenancy request and disruption inquiry lands on service teams staffed for the median day; an agentic frontline that answers in Cantonese, English or Mandarin, resolves routine transit and tenancy service in-conversation, and scales instantly when incidents spike is how a publicly scrutinized operator keeps service standards visibly rising while costs don't.

Entry use case
Passenger service hotline (fares, Octopus-linked queries, lost property, service status)
Expected outcome
Resolve routine passenger inquiries in-conversation and absorb incident-day contact spikes without surge staffing, with measurable wait-time reduction.
Recommended next step
Workshop with customer experience leadership: baseline hotline volumes and incident-day multipliers, then scope a Scale pilot on the passenger service line.
What we understand

MTR Corporation's operating reality

MTR Corporation operates Hong Kong's metro network with millions of passenger journeys daily, alongside a rail-plus-property model spanning shopping malls, offices and residential developments.

Public fact

MTR holds a majority stake in Octopus Holdings, whose stored-value card underpins fares and everyday payments across the city — making MTR adjacent to enormous payment-linked service volume.

Public fact

Service disruptions draw intense public, media and Legco scrutiny, with fare-adjustment mechanisms and performance penalties keeping service standards politically visible.

Public fact

Tourist inflow from the mainland and overseas adds Mandarin- and English-heavy inquiry volume on fares, routes and airport services.

Reasoned inference

Property management and mall tenancy generate a parallel service stream — maintenance requests, leasing inquiries, resident services — likely handled by separate teams with separate stacks.

Seller hypothesis — validate

Lost-property and fare-dispute contacts are high-volume, low-complexity classes ideal for in-conversation resolution.

Reasoned inference

Validate with the account team before outreach: Actual hotline and station-inquiry volumes and incident-day multipliers · How property-management service is organized and its contact volume · Octopus Holdings' separate service estate and whether it's in scope · Public-sector-style procurement requirements and timelines

Build vs buy

Why we have a right to win here

Buy-led target

Limited internal ability or appetite to build the core platform — strong candidate for the packaged solution

Evidence: MTR is an engineering-led operator in rail systems, not software — its digital estate is vendor-built, it has no LLM program, and trilingual conversational AI for passenger and tenant service is a clear governed procurement.

Why they won't build the full stack: Corporate engineering is consumed by railway assets, signalling modernization and property development; building conversational AI in-house is outside every mandate, while a bought platform with human gates delivers visible service improvement the fare-adjustment-era public narrative needs now.

What management is signalling

MTR operates under fare-adjustment and service-performance mechanisms that keep fares regulated and service standards publicly scrutinized, while property development funds the model.

Reported factrecent annual reports · 2025

GTM implication: Revenue is regulated but cost-to-serve is not — sell measurable service-cost reduction with visibly better passenger service as the politically safe efficiency lever.

Tourism recovery and mainland visitor flows are lifting inquiry volumes in Mandarin and English across the network.

Inferencerecent investor communications (validate) · 2025-2026

GTM implication: Trilingual elasticity serves the visitor economy Hong Kong is publicly courting — validate visitor-inquiry share with the account team.

What already exists (don't pitch this)
  • MTR Mobile app with journey planning and notifications
  • Station staff and customer service centres
  • Passenger hotline and web inquiry forms
  • Majority stake in Octopus Holdings' payment ecosystem
What customers still can't do end-to-end (pitch this)
  • →In-conversation resolution — lost property, fare disputes and requests still require callbacks
  • →Elastic capacity for incident-day inquiry spikes
  • →Trilingual conversational voice beyond scripted IVR
  • →Unified context across rail, property and township service streams
Opportunity map

Where agentic communications pays off first

WorkflowWhy it matters hereValueComplexitySpeedChannels
Passenger service hotline
Routine passenger service resolved in-conversation in three languages; incident spikes absorbed elastically.
Fares, Octopus-linked queries, lost property and service status are the structural volume of a system moving millions daily.
Friction today: Peak and incident-day calls queue; tourists hit language mismatches; lost-property follow-ups repeat for days.
VoiceApp chatWeb
Incident and disruption communication
Consistent, live service-status conversations at unlimited capacity; staff freed for on-platform response.
Disruption response defines MTR's public reputation and regulatory standing more than any other touchpoint.
Friction today: Incident-day inquiry spikes melt hotline capacity exactly when accurate, calm answers matter most.
App chatVoiceSMS
Property and tenant services desk
Requests logged, tracked and statused in-conversation; management offices work from structured queues.
Malls, offices and residences above the stations generate maintenance, leasing and resident-service volume year-round.
Friction today: Tenant requests route through management-office phone trees and paper-era processes.
VoiceWhatsAppWeb
Watch the change

Passenger service hotline (fares, Octopus-linked queries, lost property, service status): today vs the agentic model

Scenario: A signalling fault slows the Tsuen Wan line at 8am; commuters get accurate delay-and-alternative-route answers in Cantonese instantly instead of queueing on the hotline, a Beijing tourist gets airport-express rebooking guidance in Mandarin, and the service team works the platform instead of the phones.
Today
same interaction, two worlds
Agentic layer
First-contact resolution
deferred via tickets
in-conversation actions
Platform capability
Cost per contact
$13.50 median assisted
$1.84 median self-service
Benchmark
QA coverage
1–2% sampled
100% scored
Platform capability
Sources & assumptions
  • · First-contact resolution: Process design: agent acts in systems of record
  • · Cost per contact: Gartner customer service cost benchmarks, 2024
  • · QA coverage: Platform capability: every interaction logged and evaluated
  • · Gartner, customer service cost benchmarks (2024): $13.50 median assisted vs $1.84 self-service per contact
  • · McKinsey, digital-first collections research: 20–25% NPL reduction among leaders; up to 40% opex reduction with gen AI
  • · Baymard Institute: ~70% average cart abandonment (meta-analysis)
  • · IAMAI–Kantar via IBEF (2025): 900M+ Indian internet users; 98% consume Indic-language content
  • · LeadSquared and vendor funnel studies: 78% of students choose the first institution to respond (directional, vendor data)
  • · HDI / ITSM operator benchmarks: $15–25 per L1 ticket; 40–60% of L1 volume is resets/status (validate per customer)
  • · Conventional-flow wait times and volumes are typical operator patterns — assumptions to replace with the customer's own baseline
  • · Agentic-flow behaviors (context retention, 100% logging, in-line policy checks) are platform capabilities, not projections
Recommended solution

One integrated stack, opinionated for this account

Channels · Tilicho Labs
VoiceApp chatWebSMSWhatsApp

Voice & channel orchestration, telephony, conversational execution, session/state, routing, integration build. Capability coverage validated during implementation.

Intelligence · Google Cloud
Gemini reasoningEnterprise groundingWorkflow agentsMulti-agent orchestrationGoverned actionsEvaluation & analytics
Systems · MTR Corporation
Fare systemsLost propertyService status feedsOperations control feedsService statusCRMProperty management systemsWork-order systems

API access to these systems is the critical-path dependency.

Trust & languages
CantoneseEnglishMandarin

Identity-bound sessions, policy-bounded actions, 100% audit logging, human approvals at defined points, in-tenant intelligence.

Business case

The economics, with your numbers

Addressable monthly interactions700K
Seller assumption — replace in discovery
Current cost per interaction ($)$5.0
Industry benchmark scale — validate
Automation / assistance rate (%)55%
Seller assumption — pilot proves this
$3.5M
Current operating cost / mo
$21.5M
Modelled gross benefit / yr
0.1 mo
Payback on Scale
1300%
3-yr ROI (modelled)
Automated/assisted interactions per month385K
Modelled AI run-cost per month (usage + cloud, system estimate)$135K
New monthly operating cost$1.7M

All figures are modelling estimates from the labeled inputs above — nothing here is customer-provided yet. The pilot's first job is replacing these assumptions with MTR Corporation's measured baseline. Package price covers implementation only; recurring usage billed separately.

Recommended package

Scale — $100K implementation

Scale · $100K · A multi-channel production deployment10–14 weeks to production across priority workflows

Why this package for MTR Corporation: Passenger service plus property-tenant servicing are two distinct, well-bounded workflow families across one brand — multi-workflow Scale scope with clean integration boundaries.

Included
  • 4–6 channels
  • 2–3 priority workflows
  • Multiple enterprise integrations
  • API credential & security setup
  • Advanced orchestration
  • Multilingual support
  • Agent Assist / human escalation
  • Production analytics
  • Expansion roadmap
Not included
  • ✕Usage & consumption (billed separately)
  • ✕Enterprise-wide governance build-out
  • ✕Multi-BU rollout
Recurring costs (separate from the package)

Packages cover implementation and integration only. Recurring costs are billed separately: Tilicho Labs platform usage (~$0.15/call-min indicative, usage only), Google Cloud consumption, telephony/carrier charges, managed operations, and support & optimization. No package includes unlimited usage.

Customer resources required
  • · API access + credentials for: Fare systems, Lost property, Service status feeds
  • · A named business owner for passenger service hotline (fares, octopus-linked queries, lost property, service status)
  • · Security review counterpart and policy sign-off (Fare systems scope)
  • · Baseline metrics for the pilot's success thresholds
Executive messages

What to say to whom

CEO

“MTR's licence to operate is public confidence; service that answers instantly in three languages — especially on the bad days — is confidence made tangible, at a cost profile the fare mechanism doesn't punish.”

CIO / CTO

“A governed agent layer over service-status, fare and property APIs consolidates fragmented hotlines into one auditable platform — bounded integrations, no core-system change.”

COO

“You staff for the median day and get judged on the incident day; elastic capacity absorbs the spike while your people handle the platform, not the phones.”

Head of Customer Experience / Operations

“Lost property, fares and status are your volume; resolving them in-conversation transforms wait times and lets station staff serve passengers face to face.”

Chief Risk / Compliance Officer

“PDPO-aligned processing, approved-language enforcement on incident communication, 100% logging — consistent public messaging with an audit trail, even at spike volume.”

CFO / Procurement

“Fare revenue is regulated; costs are not — measured cost per resolved contact across rail and property service is a controllable line this pilot quantifies in one quarter.”

Outreach

Pre-built offer emails for MTR Corporation

Written from this account's own research — the strategic signal, the capability gap, the entry workflow, and the modelled economics — not a mail-merge template. Pick the moment and the persona, edit anything, then copy or open in your mail client.

Moment in the deal
Cold outreach — no prior conversation
Who it's addressed to
Cares about: The workflow itself and its daily failure modes
Register
Length
Draft — edit freely before sending
Open in mail client

Customer-safe by construction: drafts are composed only from customer-facing fields. Account tier, build-vs-buy classification, priority score, internal routing, and partner-commercial detail are not inputs to the composer, so they cannot appear in a draft. Money figures are always framed as modelled from the customer's own volumes. Read before sending — you own what goes out.

The pursuit

Tier 2 — high-potential incubation

Why this tier

The rail-plus-property operator that moves millions of passengers daily and manages malls, offices and residences across Hong Kong — Octopus-adjacent service volume across transit, tenancy and township life, under permanent public and Legco scrutiny.

Recommended next step

Workshop with customer experience leadership: baseline hotline volumes and incident-day multipliers, then scope a Scale pilot on the passenger service line.

Entry: Passenger service hotline (fares, Octopus-linked queries, lost property, service status) · Scale package · 10–14 weeks to production across priority workflows. Human fallback throughout; success thresholds agreed before build.

Start the pursuit

Research-based priority-account universe assembled from public information, market scale, communication volume, and solution fit. This is NOT an authoritative list of top Google Cloud customers; existing Google Cloud relationships are noted only where publicly reported. Validate every account with the account team before outreach.