What we build
Customer-grade messaging — engineered for the operations team.
Each capability is a production component — not a copy-paste template — wired to your gateways and TMS, governed by consent and frequency policy, and monitored continuously.
Live, parcel-level ETA with confidence band
Telematics, traffic, and TMS milestones feed an ETA model that publishes a per-parcel arrival window with a confidence band. Customers see the same number the dispatcher sees — and an honest range when the road is unpredictable.
Multi-channel notifications · SMS, WA, email, push
WhatsApp Business API, SMS, email, push, and in-app — orchestrated through a single policy layer. The customer's preferred channel and language is respected; the rest fall back automatically when the first attempt doesn't land.
Exception triage + proactive disruption messaging
Delays, attempted-deliveries, and address fails are classified by severity and routed with the right tone — not a generic apology. Customers hear about the problem before they have to ask, with a next step ready.
Self-service reschedule + delivery options
Drop-point change, neighbour delivery, and time-slot swap are all served through a tap-and-confirm portal. The cases that don't need a human are resolved by the customer in under a minute — the rest are escalated cleanly.
Sentiment + NPS feedback loop
Replies, post-delivery NPS, and free-text feedback are scored in multiple SEA languages and wired back into routing, send-time, and the next message. Negative signals reach the support lead before the ticket queue does.
Frequency-cap + consent-aware messaging
PDPA, GDPR, and TCPA-aligned consent records, opt-out chains, and per-customer frequency caps are enforced at every send. The audit trail tracks the rule that gated the message — not just the message itself.
Who we message for
One engine, every delivery motion.
Same orchestration, exception triage, and feedback layer — tuned per delivery model. Shared classifier stack, per-fleet adapters, and per-customer language and channel preferences carried across journeys.
3PL last-mile carriers
Last-mile carriers running urban and inter-city routes. Live ETAs, attempted-delivery proactive messaging, and self-service reschedule at the scale of tens of thousands of parcels per day.
Quick-commerce + grocery delivery
Sub-2-hour grocery and quick-commerce flows where the customer is waiting at home. Minute-precision ETAs, fallback-channel cascades, and apology-with-credit playbooks when the rider runs late.
Marketplace fulfilment
Lazada, Shopee, TikTok Shop, and direct-to-consumer fulfilment partners. Branded comms in the marketplace's language and tone, with merchant-level deliverability and CSAT visibility.
Cross-border parcel · regional
Regional cross-border parcel networks where transit spans multiple jurisdictions. Customs-hold messaging, multi-language updates, and customs-clearance ETAs that update as the parcel moves.
Field-service appointments
Utilities, telco, and repair-service appointments. Two-way SMS / WhatsApp confirmations, en-route ETAs, technician-arrival notifications, and post-visit feedback wired to the dispatch system.
Returns + reverse logistics
Return-pickup scheduling, drop-off-location guidance, refund-status updates, and condition-report follow-ups — closing the loop on the experience the customer remembers most.
Model families we deploy
No single model handles every message. So we compose.
ETA prediction, exception classification, sentiment + intent, and send-time optimisation each have their own model family — composed into one orchestration pipeline with version control at every step.
ML model that predicts per-parcel arrival from live vehicle telematics, route-stage features, traffic, and historical hub-to-stop times. Publishes a P90 band, not just a midpoint, so the customer sees an honest range.
ML classifier scores delivery exceptions (delay, attempted-delivery, address-fail, return-to-sender) by severity and recommends the channel and tone — friendly apology vs urgent action vs neutral update.
LLM-backed NLP across EN, BM, ID, TH, VI, and ZH. Scores incoming messages and post-delivery feedback for sentiment and intent so the right reply (or escalation) lands in seconds — local-language fluency baked in, not bolted on.
Contextual-bandit ML model that learns the engagement window and channel mix that works for each customer cohort by region, age band, and prior responses. Cuts wasted sends and lifts read-rates without raising frequency.
Data sources wired into every message
Every feed that moves the conversation — integrated.
Pulled in parallel, normalised into one event schema, governed by consent and frequency policy, and audit-logged alongside the channel and template that produced the customer touch.
Explainability, not just delivery
Every message carries its reasoning. For the customer. For the auditor.
Every channel choice, frequency-cap decision, and exception classification is accompanied by the rule that produced it, the consent record it relied on, and the template version that fired — generated at send time, indexed for audit.
- Channel + tone choice cited per send
- Consent record traced to the source of truth
- Frequency-cap decisions logged with reason code
- Sign-off chain on every template + variant
Frameworks we align to
Why Axccelerate for customer comms
Not a notification vendor.
A customer-comms stack.
A vendor gives you a template editor. Our stack gives you live ETAs, exception triage, sentiment routing, multi-language tone, and the consent-aware orchestration a real CX team actually runs on.
Pricing
Priced to your channel mix, not your message volume.
Comms deployments are custom — we scope against your gateways, languages, and exception playbook before quoting.
Glossary
The vocabulary behind every customer touch.
A quick reference for the terms that show up in customer comms — the language your operations, support, and CX teams will all use.
- ETA conf. band
- ETA confidence band
An honest arrival window — not just a midpoint — that reflects the model's uncertainty given live traffic, route stage, and historical hub-to-stop variance.
- Frequency cap
- Send-rate ceiling
A per-customer, per-channel ceiling on how many messages may be sent in a rolling window. Hits drive deferral, channel substitution, or skip — never silent over-send.
- Opt-out chain
- Cross-channel suppression
When a customer opts out of one channel, the suppression cascades according to policy — preventing the same message reappearing in email after a WhatsApp opt-out.
- Sender rep.
- Sender reputation
A score (per domain, per gateway) that tracks how likely the customer's inbox or carrier will accept your messages. Driven by complaint rates, bounces, and engagement.
- Deliverability
- Inbox + carrier acceptance
The end-to-end probability that a sent message lands where the customer reads it. Includes domain warming, template approval, carrier filtering, and recipient-side spam.
- Sentiment cl.
- Sentiment classifier
An NLP model that scores incoming customer text — replies, NPS verbatims — for positive, neutral, or negative sentiment. Per-language for SEA accuracy.
- Intent class.
- Intent classification
Classifies what a customer is trying to do — reschedule, complain, ask for status, request refund — so the right next action (self-serve link or escalation) lands fast.
- Multi-lang NLP
- Multi-language NLP
Natural-language processing tuned for South-East Asian languages — Malay, Indonesian, Thai, Vietnamese, Chinese — with locale-specific tone and politeness models.
- Send-time opt.
- Send-time optimisation
Picks the moment of day each customer cohort is most likely to engage, learnt from prior reads, replies, and conversion. Cuts waste without raising frequency.
- Exc. template
- Exception template
A pre-approved message template — per language, per severity, per channel — used for delivery exceptions like delays, attempted-deliveries, and address fails.
- Deliver-attempt
- Delivery attempt
A discrete attempt by a courier to deliver a parcel. Failed attempts trigger proactive customer messaging and a self-service reschedule offer rather than a silent retry.
- Drop-point
- Alternate drop location
A locker, partner store, or neighbour address the customer can divert a parcel to in lieu of home delivery — surfaced inline on attempted-delivery messages.
- Neighbour deliv.
- Neighbour-handoff delivery
A consented delivery left with a named neighbour or building reception. Requires explicit per-parcel approval — captured through self-service rather than driver discretion.
- NPS
- Net Promoter Score
A simple 0-10 customer-loyalty score collected post-delivery. Tracked as a 24h-rolling pulse so dips show up in hours, not next month's report.
Your customer-comms layer, engineered.
30-minute scoping with a senior engineer and a customer-experience specialist. You'll leave with a channel map, consent plan, and realistic timeline — not a sales pitch.