SEA regionalLogistics / last-mile parcel networkScale · $100K
Ninja Van

Two million parcels a day earn their margin at the last doorstep: agentic delivery recovery for Ninja Van's network

Deploy agentic failed-delivery recovery, consignee communication, and shipper support across Ninja Van's six markets — on the Google Cloud platform it already runs — turning delivery exceptions into resolved conversations before they become RTOs.

Entry use case
Failed-delivery resolution & consignee self-service
Expected outcome
Measurable first-attempt-success lift and RTO reduction via instant, multilingual post-failure conversations
Recommended next step
Scope a two-market failed-delivery recovery pilot (Malaysia, Philippines) with first-attempt-success lift as the primary metric.
What we understand

Ninja Van's operating reality

Ninja Van is a Singapore-headquartered last-mile logistics network covering Singapore, Malaysia, Indonesia, Thailand, Vietnam and the Philippines, publicly cited as handling on the order of two million parcels a day at peak.

Public fact

Ninja Van's engineering platform publicly runs on Google Cloud — its use of GKE and Google Cloud infrastructure is documented in public engineering material.

Public fact

Failed first attempts and COD rejections are the core margin leaks of SEA last-mile economics; every percentage point of first-attempt success moves network profitability.

Reasoned inference

Shipper support (pickup scheduling, claims, COD remittance queries) is a second contact universe that gates volume retention from e-commerce clients.

Reasoned inference

E-commerce clients would pay for branded proactive delivery communication as a premium service — an agentic layer could become a Ninja Van revenue product, not just a cost tool.

Seller hypothesis — validate

Ninja Van's platform publicly runs on Google Cloud (GKE and related infrastructure, documented in public engineering content) — the agentic layer lands on infrastructure and billing relationships that already exist.

Publicly reported Google Cloud relevance

Validate with the account team before outreach: Real-time failed-attempt event availability from the ops platform · RTO cost model and avoidable-failure share by market · Shipper appetite for branded proactive-delivery communication as a paid product

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: Ninja Van's engineering is strong but concentrated on routing, sortation, and network-ops systems on Google Cloud — not conversational AI. With a publicly reported push toward profitability, it buys outcome-priced layers that move first-attempt success rather than staffing a platform team.

Why they won't build the full stack: Six languages of consignee voice and chat is a bought capability; every engineering hour spent building it is an hour not spent on the network-economics systems that are the company's actual moat. RTO recovery priced per avoided failure needs no build case at all.

What management is signalling

Reported cost restructuring and a profitability push across the network as e-commerce logistics pricing normalizes regionally.

Inferencerecent investor communications (validate) · 2025

GTM implication: Price against the fully loaded cost of a failed delivery times avoidable RTOs per month — a margin story that fits the profitability narrative exactly.

What already exists (don't pitch this)
  • Parcel tracking systems and event webhooks
  • Driver and rider apps with delivery-attempt scans
  • Shipper portal and claims processes
  • Google Cloud engineering estate (GKE)
What customers still can't do end-to-end (pitch this)
  • →Minutes-fast post-failure conversations with consignees
  • →Multilingual voice across six markets from one deployment
  • →Structured delivery-preference capture feeding routing
  • →Automated claims intake validated in-flow for shippers
Opportunity map

Where agentic communications pays off first

WorkflowWhy it matters hereValueComplexitySpeedChannels
Failed-delivery resolution
Consignee engaged within minutes of a failed attempt in their language, address/slot/COD issue fixed conversationally, avoidance attributed.
The economics of the entire network concentrate at the failed doorstep; minutes-fast recovery converts RTOs into completed deliveries.
Friction today: Driver notes are cryptic; consignees learn of failures hours later; second attempts repeat the same failure.
WhatsAppSMSVoice
Consignee tracking & delivery preferences
Conversational tracking with proactive exception notices; structured preference capture that feeds routing.
Where-is-my-parcel contacts scale with volume; preference capture (gate codes, safe-drop) prevents failures upstream.
Friction today: Tracking pages answer poorly; preferences live in driver memory.
WhatsAppWeb chat
Shipper support & claims
Shipper-recognized support with claim intake validated in-flow and remittance status grounded in finance systems.
E-commerce clients churn networks over claim friction and COD remittance opacity.
Friction today: Shipper tickets queue behind consumer volume; claims bounce on documentation.
Web chatEmailVoice
Watch the change

Failed-delivery resolution & consignee self-service: today vs the agentic model

Scenario: A Bangkok consignee misses a delivery while at work; ninety seconds after the failed scan she picks an evening slot and drops a gate code on WhatsApp — first-attempt failure, second-attempt certainty.
Today
same interaction, two worlds
Agentic layer
Contacts per delivery incident
3–4 across channels
1 proactive thread
Platform capability
Cart abandonment context
~70% average
recoverable via consent-based outreach
Benchmark
Cost per contact
$13.50 median assisted
$1.84 median self-service
Benchmark
QA coverage
1–2% sampled
100% scored
Platform capability
Sources & assumptions
  • · Contacts per delivery incident: Process design: exception detected before contact
  • · Cart abandonment context: Baymard Institute meta-analysis
  • · 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
WhatsAppSMSVoiceWeb chatEmail

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 · Ninja Van
Last-mile ops platformRoute planningOMS integrationsTracking systemsShipper portalClaimsFinance/remittance

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

Trust & languages
EnglishBahasa IndonesiaThaiVietnameseBahasa MalaysiaTagalog

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 interactions3.0M
Seller assumption — replace in discovery
Current cost per interaction ($)$0.8
Industry benchmark scale — validate
Automation / assistance rate (%)55%
Seller assumption — pilot proves this
$2.4M
Current operating cost / mo
$8.9M
Modelled gross benefit / yr
0.1 mo
Payback on Scale
127%
3-yr ROI (modelled)
Automated/assisted interactions per month1.7M
Modelled AI run-cost per month (usage + cloud, system estimate)$578K
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 Ninja Van'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 Ninja Van: Consignee recovery, shipper support, and COD workflows across six markets and as many languages constitute a multi-workflow, multi-market Scale deployment on an already-friendly cloud estate.

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: Last-mile ops platform, Route planning, OMS integrations
  • · A named business owner for failed-delivery resolution & consignee self-service
  • · Security review counterpart and policy sign-off (Last-mile ops platform scope)
  • · Baseline metrics for the pilot's success thresholds
Executive messages

What to say to whom

CEO

“Ninja Van's next margin story is operational: every recovered RTO is pure network profit, and a branded proactive-delivery experience becomes a product your e-commerce clients pay for.”

CIO / CTO

“You already run on Google Cloud — Gemini Enterprise agents grounded in your ops platform extend the same estate, and Tilicho Labs delivers the omnichannel communications layer.”

COO

“Recovery conversations start within minutes of a failed scan, in six markets' languages, and structured preference capture stops repeat failures at the same doorsteps.”

Head of Network Operations

“Second attempts stop being blind: the conversation fixes the address, slot, or COD readiness first, and your first-attempt-success dashboards show it within weeks.”

Chief Risk / Compliance Officer

“Consignee outreach honors each market's data-protection regime — PDPA variants, PDP, Decree 13 — with consent management and complete logs built into the platform.”

CFO / Procurement

“Price it against your own number for a failed delivery's fully loaded cost times avoidable RTOs per month — on cloud commercials you already have in place.”

Outreach

Pre-built offer emails for Ninja Van

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

SEA-wide parcel network handling roughly two million parcels daily across six markets, publicly running on Google Cloud — failed-delivery resolution and shipper support are its economics in miniature, and the cloud fit is already proven.

Recommended next step

Scope a two-market failed-delivery recovery pilot (Malaysia, Philippines) with first-attempt-success lift as the primary metric.

Entry: Failed-delivery resolution & consignee self-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.