ANZEnergy retail & transitionScale · $100K
Origin Energy

The transition's bills need translating — agentic energy service for Origin's Kraken-powered retail book

Origin retails energy to millions of accounts in a market where comparison sites make churn a weekly threat and the energy transition makes bills steadily stranger — solar feed-in, batteries, EV tariffs, demand response; having moved its book onto Kraken, Origin has the modern system of record but still answers transition-era questions with contact-center labor; an agentic frontline grounded in Kraken that explains bills plainly, executes tariff moves in-conversation and saves churn-risk customers at full coverage completes the platform bet with conversation-layer economics.

Entry use case
Billing explanation and tariff service line
Expected outcome
Resolve bill-explanation and tariff contacts in-conversation with churn-risk saves at full coverage, cutting cost per contact and measured churn together.
Recommended next step
Workshop with retail leadership: baseline bill-explanation and churn-driver contact data from Kraken, then scope a Scale pilot on the billing and retention lines.
What we understand

Origin Energy's operating reality

Origin Energy is one of Australia's largest energy retailers, with a major stake in Octopus Energy and its retail operations migrated onto the Kraken platform.

Public fact

Origin's FY25 reporting highlighted Kraken's global growth — contracted accounts up sharply — underlining the group's strategic bet on retail technology.

Public fact

Australian energy retail is churn-intensive: regulated default offers, comparison sites and cost-of-living scrutiny keep switching pressure and political attention permanently high.

Public fact

Energy-transition products — rooftop solar, batteries, EV plans, virtual power plants — multiply tariff complexity and bill-explanation contact volume.

Reasoned inference

Kraken's clean API surface makes conversational integration materially easier than legacy utility stacks — a delivery advantage over most energy-retail deployments.

Reasoned inference

Hardship and payment-difficulty conversations are growing with energy prices and carry regulatory conduct obligations.

Seller hypothesis — validate

Validate with the account team before outreach: Kraken integration surface and what Octopus's own AI roadmap already claims · Actual churn rates, save-desk coverage and bill-shock contact volumes · AER conduct constraints on automated retention and hardship conversations · Whether the Octopus relationship channels conversational AI decisions through Kraken's roadmap

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: Origin's technology strategy runs through its Octopus/Kraken stake — it buys platform capability through partnership rather than building internally; conversational AI grounded in Kraken is a natural extension of that model, needing a partner for voice quality, workflows and delivery while respecting whatever Kraken's own roadmap provides.

Why they won't build the full stack: Origin deliberately chose platform partnership over internal retail-tech build when it adopted Kraken; reversing that logic for voice AI makes no sense, while a partnered frontline grounded in Kraken delivers churn and cost-to-serve results inside the platform strategy already declared to investors.

What management is signalling

Origin's FY25 results highlighted Kraken's contracted accounts growing about 45% to 74 million globally, with the Octopus stake central to the investment case.

Reported factFY25 annual results · Aug 2025

GTM implication: The group's own story is retail-platform advantage — sell the conversational layer as the domestic proof of the platform bet investors already price.

Cost-of-living scrutiny and energy-price politics keep retail conduct, hardship handling and churn under continuous public attention.

Inferencerecent investor communications (validate) · 2025-2026

GTM implication: Frame automation as better explanation and fairer treatment at scale — conduct-first positioning in a politically watched market.

What already exists (don't pitch this)
  • Origin app with billing and usage self-service on Kraken
  • Retail book migrated to the Kraken platform
  • Solar, battery, EV and VPP product portfolio
  • Save desks and churn-model-driven outreach at limited coverage
What customers still can't do end-to-end (pitch this)
  • →Plain-language bill explanation at contact-center scale
  • →Full-coverage retention conversations at expiring benefit periods
  • →In-conversation tariff moves and product enrollment
  • →Specialist-grade transition-product guidance that scales
Opportunity map

Where agentic communications pays off first

WorkflowWhy it matters hereValueComplexitySpeedChannels
Billing explanation and tariff service
Bills explained line by line from Kraken data; tariff moves executed in-conversation; churn triggers defused at first contact.
Bill shock and tariff confusion are the top contact drivers and the top churn triggers in energy retail.
Friction today: Transition-era bills defeat IVRs; explanations queue for humans and vary by agent.
VoiceApp chatWeb
Churn-risk retention and win-back
Full at-risk coverage with policy-bounded offers; save rates attributed weekly.
Comparison-site switching makes every expiring benefit period a retention moment; coverage decides the churn number.
Friction today: Save capacity reaches a fraction of at-risk accounts; most switches happen without a conversation.
VoiceSMSApp chat
Solar, battery and EV product support
Grounded product guidance and enrollment in-conversation; transition adoption measured per campaign.
Transition products are the growth strategy and the most explanation-heavy relationships in the book.
Friction today: Feed-in, VPP and EV-tariff questions need specialist knowledge that doesn't scale by hiring.
App chatVoiceWeb
Watch the change

Billing explanation and tariff service line: today vs the agentic model

Scenario: A customer with new rooftop solar calls about a bill that didn't drop as expected; the agent walks through the Kraken data — usage shifted to evenings, feed-in credited correctly — recommends the time-of-use tariff that fits her pattern, switches her in-conversation and books a battery consult — a churn call converted into a deeper relationship.
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 chatWebSMS

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 · Origin Energy
KrakenBillingCRMChurn modelsOffer matrixDER/VPP platformsKnowledge base

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

Trust & languages
English

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 interactions1.3M
Seller assumption — replace in discovery
Current cost per interaction ($)$6.0
Industry benchmark scale — validate
Automation / assistance rate (%)55%
Seller assumption — pilot proves this
$7.8M
Current operating cost / mo
$48.5M
Modelled gross benefit / yr
0.0 mo
Payback on Scale
1595%
3-yr ROI (modelled)
Automated/assisted interactions per month715K
Modelled AI run-cost per month (usage + cloud, system estimate)$250K
New monthly operating cost$3.8M

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 Origin Energy'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 Origin Energy: Billing service plus retention outreach plus solar/EV product support are multi-workflow Scale scope over a single modern platform integration — unusually clean delivery 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: Kraken, Billing, CRM
  • · A named business owner for billing explanation and tariff service line
  • · Security review counterpart and policy sign-off (Kraken scope)
  • · Baseline metrics for the pilot's success thresholds
Executive messages

What to say to whom

CEO

“Origin bet on Kraken as the retail platform of the transition; a conversational frontline grounded in it is the customer-facing half of that bet — the experience layer that makes the platform advantage visible.”

CIO / CTO

“Kraken's API surface makes this the cleanest conversational integration in Australian energy — a governed agent layer over one modern platform, not a legacy-stack archaeology project.”

COO

“Transition products multiply explanation-heavy contacts faster than any hiring plan; grounded automation is the only service model that scales with the product roadmap.”

Head of Retail

“Churn is decided in bill-shock moments and expiring benefit periods; full-coverage conversations at both — with offer discipline — moves the retention number the market watches.”

Chief Risk / Compliance Officer

“AER conduct obligations, hardship routing to humans, approved-offer enforcement and 100% logging — retail conduct evidence at a standard the regulator's focus rewards.”

CFO / Procurement

“Cost-to-serve per account and churn are the two retail levers; the pilot measures both against baseline in a quarter, with usage-based run cost.”

Outreach

Pre-built offer emails for Origin Energy

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

One of Australia's largest energy retailers, running its retail book on Kraken through its Octopus Energy stake — a technology-forward retailer in a market of brutal churn, cost-of-living scrutiny and energy-transition complexity from solar, batteries and EVs.

Recommended next step

Workshop with retail leadership: baseline bill-explanation and churn-driver contact data from Kraken, then scope a Scale pilot on the billing and retention lines.

Entry: Billing explanation and tariff 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.