KoreaTelecomScale · $100K
LG Uplus

From ixi-O to the whole frontline — extending LG Uplus's public Gemini bet to its own service queues

LG Uplus already chose Gemini for its consumer AI agent ixi-O, which makes the strategic argument for a Gemini-powered service frontline internal consistency rather than vendor persuasion; deploying agentic automation on its billing, retention and technical queues turns the challenger carrier's AI-agent brand into operational economics — the third player's classic path to margin parity with SKT and KT.

Entry use case
Billing and plan service line
Expected outcome
Cut cost per contact on routine billing volume and prove frontline economics that extend the existing Gemini relationship into service operations.
Recommended next step
Strategy-alignment session with AX and customer-service leadership: position the frontline deployment as the operational extension of the announced Gemini partnership, then baseline the billing line for a Scale pilot.
What we understand

LG Uplus's operating reality

LG Uplus, the LG-affiliated #3 Korean carrier, has publicly committed to transforming into an 'AX company', with announced multi-billion-dollar AI investment plans.

Public fact

LG Uplus's ixi-O AI call assistant publicly integrates Google's Gemini models under an announced partnership, and its ixi-GEN model builds on LG Group's Exaone LLM for telecom-specific services.

Public fact

As the #3 carrier, LG Uplus runs structurally thinner margins than SKT and per-subscriber economics that reward cost automation more than either rival.

Reasoned inference

The consumer AI-agent strategy (ixi-O on smartphones) is a brand differentiator aimed at younger subscribers — service-experience quality is part of the same positioning.

Public fact

Bundle billing across mobile, broadband and IPTV generates the same legacy-complex volume as its larger rivals but with less internal platform capacity to automate it.

Reasoned inference

Retention outreach likely covers only a fraction of expiring-contract cohorts on current outbound capacity.

Seller hypothesis — validate

LG Uplus has publicly announced a partnership with Google to integrate Gemini models into its ixi-O AI call assistant — a named, public Google AI relationship this proposal extends into service operations.

Publicly reported Google Cloud relevance

Validate with the account team before outreach: Scope and exclusivity of the existing Google/Gemini partnership around ixi-O · Which service workflows LG Uplus plans to automate with ixi-GEN internally · Retention-cohort sizes and current save-desk coverage · LG Group (Exaone) platform preferences in procurement

Build vs buy

Why we have a right to win here

Partner-led target

Technically capable but needs industry workflows, integration, acceleration, or managed operations

Evidence: LG Uplus builds real AI assets — ixi-GEN on LG's Exaone, the ixi-O agent — but has publicly chosen to power ixi-O with Google's Gemini rather than build frontier models alone; that pattern is exactly partner-led: LG Uplus owns product and brand, partners supply model and platform depth, and the frontline deployment extends a partnership that already exists.

Why they won't build the full stack: The #3 carrier cannot outspend SKT's and KT's internal AI programs; its published strategy is leverage — LG Exaone plus Google Gemini plus partners — and a bought agentic frontline on that same pattern delivers margin relief quarters sooner than any internal platform could.

What management is signalling

LG Uplus has publicly committed roughly $2 billion to its AX transformation and showcased its ixi-O agent strategy — including the Gemini integration — at successive Mobile World Congress events.

Reported factpublic strategy announcements · 2024-2026

GTM implication: The frontline proposal is the operational chapter of a strategy already announced — sell continuity, not conversion.

As Korea's #3 carrier, LG Uplus faces persistent margin and ARPU pressure in a saturated market, with cost efficiency a recurring investor theme.

Inferencerecent investor communications (validate) · 2025-2026

GTM implication: Lead with per-contact economics: the thinnest-margin carrier gains the most from every automated conversation.

What already exists (don't pitch this)
  • ixi-O AI call assistant publicly powered by Gemini models
  • ixi-GEN telecom LLM built on LG Exaone
  • LG Uplus app with billing self-service
  • Announced multi-billion-dollar AX investment program
What customers still can't do end-to-end (pitch this)
  • →Agentic automation on LG Uplus's own service queues (ixi-O serves subscribers' personal calls, not the carrier's service lines)
  • →Transactional billing and plan-change depth in-conversation
  • →Full-cohort retention coverage
  • →Diagnostic triage that prevents avoidable truck rolls
Opportunity map

Where agentic communications pays off first

WorkflowWhy it matters hereValueComplexitySpeedChannels
Billing and plan service line
Billing and plan changes resolved in-conversation with transactions executed; peak absorption at usage pricing.
Routine billing is the #3 carrier's structural volume, carried at margins thinner than either rival's.
Friction today: Billing-cycle peaks melt queues; plan-change journeys break between app and phone; per-contact costs pressure a tighter P&L.
VoiceApp chatKakaoTalk
Retention and contract-renewal desk
Full expiring-cohort coverage with policy-bounded offers; port-out economics measurably bent.
In a saturated three-carrier market, expiring-contract cohorts are the revenue battlefield; coverage decides share.
Friction today: Save teams reach a fraction of at-risk subscribers; number-portability makes switching frictionless for competitors to harvest.
KakaoTalkVoiceSMS
Broadband and IPTV technical triage
Diagnosis with line data in-conversation, guided fixes, dispatches reserved for hardware failures.
Home-connectivity issues drive long handle times and truck rolls a diagnosing agent can often prevent.
Friction today: Scripted triage misdiagnoses; truck rolls dispatch for software-fixable issues.
VoiceApp chat
Watch the change

Billing and plan service line: today vs the agentic model

Scenario: A subscriber whose contract expires in three weeks gets a proactive KakaoTalk conversation; the agent reviews her usage against her plan, offers the approved renewal bundle with the family discount she qualifies for, executes the change on acceptance and schedules the ixi-O onboarding tip she asks about — a save that dialer capacity would never have reached.
Today
same interaction, two worlds
Agentic layer
Languages served
2–3 staffed
10+ in one deployment
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
  • · Languages served: Platform capability: Gemini + Chirp speech
  • · 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 chatKakaoTalkSMS

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 · LG Uplus
BSS/billingCRMSubscription managementChurn modelsOffer matrixNetwork diagnosticsField-service dispatch

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

Trust & languages
KoreanEnglish

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 interactions1.4M
Seller assumption — replace in discovery
Current cost per interaction ($)$3.0
Industry benchmark scale — validate
Automation / assistance rate (%)55%
Seller assumption — pilot proves this
$4.2M
Current operating cost / mo
$24.5M
Modelled gross benefit / yr
0.0 mo
Payback on Scale
748%
3-yr ROI (modelled)
Automated/assisted interactions per month770K
Modelled AI run-cost per month (usage + cloud, system estimate)$270K
New monthly operating cost$2.2M

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 LG Uplus'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 LG Uplus: Billing service plus retention are two urgent workflows for a #3 carrier fighting for margin; Scale's multi-channel scope fits, and the existing Google AI relationship shortens the architecture conversation.

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: BSS/billing, CRM, Subscription management
  • · A named business owner for billing and plan service line
  • · Security review counterpart and policy sign-off (BSS/billing scope)
  • · Baseline metrics for the pilot's success thresholds
Executive messages

What to say to whom

CEO

“LG Uplus told the market it is becoming an AX company and chose Gemini for its flagship consumer agent; running the same intelligence on your own frontline is the operational proof of that strategy — and the margin lever a #3 carrier needs most.”

CIO / CTO

“Your architecture already speaks Gemini through ixi-O; extending governed agentic automation to service queues rides the same model family and partnership rails — the shortest integration path in Korean telecom.”

COO

“Thinner margins make your per-contact economics the most automation-rewarded of the three carriers; elastic capacity on billing and triage cuts the cost base SKT and KT can outspend you on.”

Head of Customer Service

“Peak-day queue melt and truck rolls for software problems are your two worst numbers; a diagnosing, transacting agent attacks both in one deployment.”

Chief Risk / Compliance Officer

“PIPA-aligned outreach windows, approved-offer governance and 100% logging — retention automation with conduct evidence built in from day one.”

CFO / Procurement

“The pilot measures cost per contact and save-rate lift against your own baselines within a quarter; usage pricing means the cost curve tracks volume, not headcount plans.”

Outreach

Pre-built offer emails for LG Uplus

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 1 — immediate strategic pursuit

Why this tier

Korea's #3 carrier has publicly built its AI-agent strategy on Google's Gemini — the ixi-O call assistant integrates Gemini models under a announced Google partnership — making it the one Korean telco where a Gemini-powered frontline extends an existing, public technology bet rather than fighting an internal stack.

30 / 60 / 90-day plan
  • Day 0–30: Strategy-alignment session with AX and customer-service leadership: position the frontline deployment as the operational extension of the announced Gemini partnership, then baseline the billing line for a Scale pilot.; confirm sponsor and baseline data access; validate: Scope and exclusivity of the existing Google/Gemini partnership around ixi-O
  • Day 31–60: architecture & security review with the platform team; Tilicho Labs scoping on Voice + App chat; pilot scope signed
  • Day 61–90: Scale package kickoff; billing and plan service line pilot in build; success thresholds locked with the Head of Customer Service
Recommended next step

Strategy-alignment session with AX and customer-service leadership: position the frontline deployment as the operational extension of the announced Gemini partnership, then baseline the billing line for a Scale pilot.

Entry: Billing and plan service line · 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.