MalaysiaAviation / travel super-appScale · $100K
Capital A (AirAsia)

The airline that digitized Asian budget travel still queues its guests on chat: agentic guest support for AirAsia and MOVE

Rebuild AirAsia's guest-support economics with agentic disruption handling, refund transparency, and MOVE super-app service — on the Google Cloud estate the group already runs.

Entry use case
Disruption rebooking & refund-status resolution
Expected outcome
Absorb disruption spikes with proactive rebooking and collapse the refund-status contact class that has historically dominated complaint volume
Recommended next step
Workshop with group guest-services leadership to baseline refund-status contact volume and scope a disruption-rebooking pilot on one AOC.
What we understand

Capital A (AirAsia)'s operating reality

Capital A (formerly AirAsia Group) spans the AirAsia airlines, the airasia MOVE travel super-app, BigPay fintech, and Teleport logistics; the group's aviation consolidation under the AirAsia Group structure has been publicly executed.

Public fact

AirAsia has a publicly reported, long-standing Google Cloud relationship, with cloud and data initiatives repeatedly showcased by both companies.

Public fact

Post-pandemic refund backlogs made AirAsia's refund-status opacity a publicly visible complaint theme — the scar tissue makes refund transparency a brand-repair lever, not just a cost line.

Public fact

The existing AVA chatbot era taught the group both the value and the limits of scripted automation; guest frustration with deflection-style bots is well documented in app reviews.

Reasoned inference

MOVE's OTA ambitions (hotels, rides, bundles) add non-flight service volume the airline-shaped support organization was never designed for.

Reasoned inference

AirAsia's Google Cloud relationship is publicly reported and long-standing — the group has showcased cloud and data work with Google for years, making the platform conversation an extension, not a sale.

Publicly reported Google Cloud relevance

Validate with the account team before outreach: Current in-house chatbot roadmap and where it falls short · PSS and refund-pipeline API access across AOCs · Which market's disruption profile suits the pilot best

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: Despite the group's digital identity, its engineering is consumer-product-focused (MOVE, BigPay) and capital-disciplined after restructuring. The in-house AVA chatbot era demonstrated the limits of scripted self-build in guest support, and the long Google Cloud relationship makes buying on the existing estate the path of least resistance.

Why they won't build the full stack: Restructuring discipline caps platform-engineering spend, and guest-support economics need fixing now — before the next disruption season, not after a two-year build. Usage-based capacity also matches the spiky cost profile an LCC group cannot staff for.

What management is signalling

Publicly completed restructuring, including PN17 status resolution and aviation consolidation under the AirAsia Group structure, with cost discipline and fleet reactivation central to the investor story.

Reported factFY2024 results and restructuring announcements · 2024–2025

GTM implication: Position usage-based support capacity as restructuring-aligned: fixed service cost becomes variable, and refund transparency repairs a publicly known complaint class.

What already exists (don't pitch this)
  • AVA chatbot across support channels
  • airasia MOVE super-app
  • BigPay fintech stack
  • WhatsApp and in-app support channels on a Google Cloud estate
What customers still can't do end-to-end (pitch this)
  • →Proactive disruption rebooking before guests join queues
  • →Live, stage-by-stage refund-pipeline transparency
  • →Voice quality across six-plus operating languages
  • →Consistent policy application on compensation across AOCs
Opportunity map

Where agentic communications pays off first

WorkflowWhy it matters hereValueComplexitySpeedChannels
Disruption rebooking & communication
Affected guests messaged proactively with live rebooking options; one-tap confirmation; spike absorbed elastically.
Multi-AOC LCC operations concentrate disruption pain; lean staffing means spikes melt every channel at once.
Friction today: Guests discover delays at the gate and queue in chat behind thousands of identical questions.
AppWhatsAppEmailVoice
Refund status & case transparency
Live, stage-by-stage refund status pushed proactively; repeat contacts and regulator complaints suppressed.
The historically dominant complaint class; opacity here taxes every new booking decision.
Friction today: Cases cross airline entities and payment channels; status answers are vague by construction.
App chatWhatsAppEmail
MOVE super-app service
Product-aware resolution across flight and non-flight bookings in one conversation.
OTA-style bookings (hotels, bundles) now generate service volume needing OTA-grade support the group must build anyway.
Friction today: Flight-shaped support processes mishandle hotel and bundle issues.
App chatWhatsApp
Watch the change

Disruption rebooking & refund-status resolution: today vs the agentic model

Scenario: A KL–Bangkok cancellation triggers proactive WhatsApp rebooking for every guest; a family of five confirms the evening flight in one tap while the old queue would still be loading.
Today
same interaction, two worlds
Agentic layer
Disruption call spike
10× volume, melted queues
suppressed by proactive rebooking
Assumption
Cost per contact
$13.50 median assisted
$1.84 median self-service
Benchmark
QA coverage
1–2% sampled
100% scored
Platform capability
Sources & assumptions
  • · Disruption call spike: Operator-reported pattern (assumption); suppression measured in pilot
  • · 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
AppWhatsAppEmailVoiceApp chat

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 · Capital A (AirAsia)
PSS/reservationOps disruption feedPaymentsRefund pipelineCase managementMOVE platformPartner inventory systems

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

Trust & languages
Bahasa MalaysiaEnglishThaiBahasa IndonesiaTagalogMandarin

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 interactions2.0M
Seller assumption — replace in discovery
Current cost per interaction ($)$0.9
Industry benchmark scale — validate
Automation / assistance rate (%)55%
Seller assumption — pilot proves this
$1.8M
Current operating cost / mo
$7.3M
Modelled gross benefit / yr
0.2 mo
Payback on Scale
155%
3-yr ROI (modelled)
Automated/assisted interactions per month1.1M
Modelled AI run-cost per month (usage + cloud, system estimate)$385K
New monthly operating cost$1.2M

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 Capital A (AirAsia)'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 Capital A (AirAsia): Disruption, refunds, and MOVE service across app, WhatsApp, and voice — multi-airline AOCs and multiple languages — need a multi-workflow deployment; the existing cloud relationship accelerates integration.

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: PSS/reservation, Ops disruption feed, Payments
  • · A named business owner for disruption rebooking & refund-status resolution
  • · Security review counterpart and policy sign-off (PSS/reservation scope)
  • · Baseline metrics for the pilot's success thresholds
Executive messages

What to say to whom

CEO

“AirAsia's story is digital disruption of travel — guest support is the chapter where the story has lagged the ambition. Agentic disruption handling closes that gap visibly, on the cloud you already bet on.”

CIO / CTO

“Your Google Cloud estate makes this an extension: Gemini Enterprise agents grounded in the PSS and refund pipeline, with Tilicho Labs handling the communications and integration layer.”

COO

“Disruption days stop being all-hands failures — proactive rebooking suppresses the spike, and your teams handle only complex itineraries and duty-of-care calls.”

Head of Guest Services / MOVE

“Refund status becomes something guests watch, not chase. That single change removes your largest complaint class and its social-media shadow.”

Chief Risk / Compliance Officer

“Consumer-protection obligations across multiple aviation jurisdictions handled with consistent policy application and complete logs — MAVCOM-style complaint reviews get evidence on demand.”

CFO / Procurement

“Support staffing sized for disruption peaks is capital wasted 350 days a year; usage-based conversational capacity matches spend to actual disruption minutes.”

Outreach

Pre-built offer emails for Capital A (AirAsia)

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 AirAsia group is one of Asia's largest LCC operations with a publicly long-standing Google Cloud relationship and an explicit digital ambition (airasia MOVE, BigPay, Teleport) — disruption support and super-app service are both structural needs.

Recommended next step

Workshop with group guest-services leadership to baseline refund-status contact volume and scope a disruption-rebooking pilot on one AOC.

Entry: Disruption rebooking & refund-status resolution · 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.