ANZAirline (low-cost carrier)Scale · $100K
Jetstar (Qantas Group)

Low fares need low-cost conversations — agentic disruption handling for Jetstar's lean-by-design operation

Jetstar's whole model strips cost from every process except one: customer support still costs the same per call as a full-service airline; an agentic frontline that rebooks, refunds and answers at software cost is the missing piece of the LCC equation — and the shield that keeps lean staffing from becoming a headline every time weather hits.

Entry use case
Disruption rebooking and refund-status service
Expected outcome
Absorb disruption-day contact spikes with proactive rebooking offers, cutting queue melt and refund-status repeat calls to a fraction.
Recommended next step
Scope a disruption-readiness pilot with Jetstar customer care: instrument one route bank, deploy proactive rebooking and refund-status flows before the next summer-storm season.
What we understand

Jetstar (Qantas Group)'s operating reality

Jetstar is the Qantas Group's low-cost carrier, flying domestic Australia and NZ, trans-Tasman and Asian routes, with a Japan joint venture — its brand promise is low fares enabled by relentless cost control.

Public fact

The Qantas Group consolidated its LCC footprint, closing Singapore-based Jetstar Asia in 2025, sharpening focus on ANZ and Japan operations.

Public fact

The Qantas Group suffered a major 2025 data incident traced through a third-party contact-center platform, putting vendor security architecture under board-level scrutiny.

Public fact

LCC unit economics make support cost-per-contact a first-order metric: a single human call can exceed the margin on a discounted fare.

Reasoned inference

Disruption events (weather, ATC, engineering) create 10x contact spikes that a lean-staffed LCC absorbs worse than a full-service carrier.

Reasoned inference

Refund and credit-voucher status queries likely form a large repeat-contact tail after every disruption wave.

Seller hypothesis — validate

Validate with the account team before outreach: Qantas Group vendor-security requirements post the 2025 incident · Current disruption-day contact multipliers and abandonment rates · Group-level CX platform decisions shared with Qantas mainline

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: An LCC's entire operating philosophy is to buy proven capability cheaply rather than build it: Jetstar runs lean engineering focused on the booking funnel and ancillary revenue, and the Qantas Group's post-incident vendor-security reset favors a small number of governed, auditable platforms over internal experiments.

Why they won't build the full stack: Jetstar has neither the engineering bench nor the economic rationale to build conversational AI — every internal build competes with fares-and-ancillary product work, and disruption-day capacity is needed now, not after a multi-year platform program; a security-vetted buy is the only path consistent with LCC cost discipline.

What management is signalling

The Qantas Group's multi-year transformation program has emphasized structural cost reduction and customer-experience remediation, with the 2025 third-party contact-center data incident putting vendor security architecture under board-level scrutiny.

Reported factQantas Group FY2025 results and public disclosures · 2025

GTM implication: Lead with governance: a security-vetted, fully-audited platform answers the board's post-incident question while delivering the LCC cost-per-contact math.

Group commentary continues to position Jetstar as the growth engine for price-sensitive and Asian leisure demand, with fleet renewal expanding capacity.

Inferencerecent investor communications (validate) · 2025-2026

GTM implication: Growth on lean staffing widens the support-capacity gap — sell elastic disruption absorption as the enabler of Jetstar's expansion without linear headcount.

What already exists (don't pitch this)
  • Jetstar app and web self-service for bookings and changes
  • Chatbot deflection on common queries
  • Disruption notification SMS/email capability
  • Qantas Group shared technology and vendor governance
What customers still can't do end-to-end (pitch this)
  • →Transactional depth — rebooking, fee-correct changes and refund status still require human agents
  • →Disruption-day surge capacity (10x spikes melt lean staffing)
  • →Japanese-language service quality at LCC cost for Jetstar Japan and Asian routes
  • →Proactive rebooking outreach before passengers join queues
Opportunity map

Where agentic communications pays off first

WorkflowWhy it matters hereValueComplexitySpeedChannels
Disruption rebooking and refund-status service
Proactive rebooking offers in-channel, live refund status, and disruption spikes absorbed without queue melt.
Disruption days define Jetstar's public reputation and are exactly when lean staffing fails hardest.
Friction today: Cancellations trigger call floods; rebooking requires agents while refund-status calls recur for weeks after.
App chatSMSVoiceWeb
Everyday booking-change and ancillary service
Self-serve changes with correct fees applied in-conversation; human queue shrinks to genuine exceptions.
Changes, baggage and seat questions are the routine volume behind the fare-plus-ancillary model.
Friction today: Fee rules and fare-difference math push simple changes into human queues.
App chatWebVoice
Japan and Asia route multilingual desk
Native-quality Japanese and English service at software cost across the network.
Jetstar Japan and Asian routes serve customers whose expectations are set by Japanese service standards, on an LCC budget.
Friction today: Japanese-language support capacity is scarce and expensive relative to LCC economics.
App chatVoice
Watch the change

Disruption rebooking and refund-status service: today vs the agentic model

Scenario: A storm cancels the evening Melbourne-Sydney bank of flights; before the gate announcement finishes, affected passengers get rebooking options in-app with one tap to confirm, refund-eligible customers see live status, and the call queue stays measured in minutes, not hours.
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
App chatSMSVoiceWeb

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 · Jetstar (Qantas Group)
PSS/reservationsDisruption managementPayments/refundsAncillary pricingPaymentsKnowledge base

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

Trust & languages
EnglishJapaneseIndonesianVietnamese

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 ($)$6.0
Industry benchmark scale — validate
Automation / assistance rate (%)55%
Seller assumption — pilot proves this
$4.2M
Current operating cost / mo
$26.1M
Modelled gross benefit / yr
0.0 mo
Payback on Scale
1580%
3-yr ROI (modelled)
Automated/assisted interactions per month385K
Modelled AI run-cost per month (usage + cloud, system estimate)$135K
New monthly operating cost$2.0M

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 Jetstar (Qantas Group)'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 Jetstar (Qantas Group): Disruption handling plus everyday booking service across app, web and voice is classic Scale scope, with clean airline-system integration boundaries (PSS, disruption feeds, payments).

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/reservations, Disruption management, Payments/refunds
  • · A named business owner for disruption rebooking and refund-status service
  • · Security review counterpart and policy sign-off (PSS/reservations scope)
  • · Baseline metrics for the pilot's success thresholds
Executive messages

What to say to whom

CEO

“Jetstar strips cost from everything except conversations; agentic service completes the LCC model — and turns disruption days from brand damage into proof the low-fare promise includes being looked after.”

CIO / CTO

“Post the group's third-party contact-center incident, a governed platform with strict data boundaries and full auditability is the architecture answer to a question the board is already asking.”

COO

“You staff for the median day and melt on the bad ones; elastic agentic capacity absorbs the 10x disruption spike without carrying that cost the other 350 days.”

Head of Customer Care, Jetstar

“Refund-status repeat calls are your longest tail after every event; live status in-channel deletes that queue, and proactive rebooking deletes most of the rest.”

Chief Risk / Compliance Officer

“Australian Privacy Act-aligned processing, tight vendor-data boundaries and 100% interaction logging — designed for a group that has just rewritten its third-party risk standards.”

CFO / Procurement

“When a human call can cost more than the fare margin, automation is the unit-economics fix; the pilot proves cost per resolved contact against your own LCC baseline.”

Outreach

Pre-built offer emails for Jetstar (Qantas Group)

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 Qantas Group's LCC lives on cost discipline — cost-per-contact matters far more here than at the full-service mainline — and disruption events routinely melt its lean support capacity across Australia, NZ and Asia.

Recommended next step

Scope a disruption-readiness pilot with Jetstar customer care: instrument one route bank, deploy proactive rebooking and refund-status flows before the next summer-storm season.

Entry: Disruption rebooking and refund-status service · 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.