Typewise for logistics

AI customer service for logistics: manage exceptions across systems

Candidate workflows for answering from shipment context and keeping exceptions with the people who own them.

Book a demo callSee how it works

Logistics service lives on exceptions. The parcel-status question is often answered by a notification or a first-level line; what reaches the second-level team is the shipment that stalled, the partner request in another language, the customer who already contacted you once and should not wait again. The useful question is not how to automate the status question but how to give the team shipment context fast and keep exception ownership clear.

Typewise agents read and write in connected CRM, ERP and ITSM systems, sensitive actions wait for approval, hand-offs carry the full context, and every action is logged. Whether any workflow below can run end to end in your organisation depends on what your systems expose and on the data behind them, so each is presented as a candidate design to evaluate, with what it needs, not as a promised capability.

Candidate workflows to evaluate

Logistics workflows to evaluate

Shipment status and proactive notifications

Candidate design

Answer where-is-my-shipment questions from tracking and order data, and support notifications written from the customer’s side with the options they can act on.

What it needs from your systems

Tracking events mapped into the service view rather than discarded; order data linked to shipments; notification templates your team owns.

What stays with people

When tracking data is missing or stale, the design says so and routes to a person rather than inventing a date. Carrier-controlled steps stay with the carrier.

Exception handling

Candidate design

Collect what happened, bring the shipment, order and partner context together, and prepare the reply or the internal task for the owning team.

What it needs from your systems

The systems holding shipment, order and partner context connected for read access; an owner per exception type.

What stays with people

Decisions on claims, penalties and commercial remedies stay with operations and account owners.

Repeat-contact prioritisation

Candidate design

Recognise a customer who has already contacted you about the same shipment and prioritise the case so they do not wait a second time.

What it needs from your systems

Customer and shipment identity matched across contacts and channels; your priority rules in a form the AI can apply.

What stays with people

Priority rules are yours; the design applies them and shows why.

Order and document intake

Candidate design

Read structured and semi-structured requests (packing lists, order documents, booking requests) and prepare the record in your system for review, removing the re-keying of long line-item lists.

What it needs from your systems

An import or write path into the target system that a person can release; document formats agreed per partner; evaluation of extraction accuracy on your real documents before anything is trusted.

What stays with people

The prepared record is released by a person until the measured error rate justifies more; deterministic business rules stay in the system of record.

Multilingual partner service

Candidate design

Let a team answer partners and customers in their language with consistent terminology, including languages a small tail of users adds to the mix.

What it needs from your systems

A customer-language policy (answer in the customer’s language or in a company language) decided before tooling; glossaries owned by the business.

What stays with people

Language policy and glossaries are business decisions; the design applies them.

Operating boundaries

What your operations team keeps

  • Identity is verified by your systems, not asserted in the conversation: account data and account changes require an authenticated customer.
  • Every action the AI may take is granted per action as read, recommend, draft or execute, and enforced where the action happens, not only in the instructions.
  • Sensitive actions wait for a named approver; hand-offs carry the full context to a person who owns the next step, including outside service hours.
  • Every step is logged, so your team can audit what was looked up, what was proposed and what was done.
  • Named relationships stay named: partner and key-account communication is assisted, with the account owner in control of what is sent.
How it is enforced

Permissions, approvals and an audit trail.

Agents read and write only in the systems and scopes you connect. Sensitive actions wait for approval, hand-offs carry the full context, and every action is logged. Hosting, access control and certifications are described on the security page.

Security and compliance →See how it works →
Rollout considerations

What a rollout has to take into account.

  1. Step 1

    Count the demand you cannot see

    If a first-level line closes simple calls without tickets, ticket volume understates both demand and the prevention opportunities. Start the baseline from all contacts.

  2. Step 2

    Deliver visible relief first

    Teams under system-migration pressure are more likely to adopt what removes work immediately, such as document intake, before they accept broader process change. Sequence accordingly, and keep the interim solution portable so it is not throwaway.

  3. Step 3

    Plan country rollout by language and consultation

    Rollout effort grows with language diversity and employee-consultation lead times, not with headcount alone. Put both in the plan before picking the order of countries.

  4. Step 4

    Agree definitions before dashboards

    Operations and employee representatives will ask what each metric and timeout means and how a time saving was derived. Have the written definitions ready at the first review.

Customer stories

Results from real deployments.

Published customer stories from logistics, transport and breakdown assistance; each describes its own setup and results, not the candidate designs above.

Logistics
Planzer boosts service efficiency by 17% with AI-assisted communication
Logistics & Transportation
STEF & Typewise: AI-Powered Customer Service at Scale
Logistics
Typewise helps DPD achieve 30% boost in efficiency using AI
Automotive Manufacturing
IVECO Accelerates Breakdown Assistance with Typewise AI
See all customer stories →

Read more articles

Is your customer data ready for an AI agent?
Implementation
Is your customer data ready for an AI agent?
Who owns the case after an AI handoff?
Automation
Who owns the case after an AI handoff?
Who owns customer-service AI after the pilot?
Strategy & ROI
Who owns customer-service AI after the pilot?

Good questions. Straight answers.

Not necessarily. A common candidate design keeps a first-level line for simple status questions and uses AI to give the second-level team context and to prepare exception cases. Where notifications and self-service are improved, some first-level demand may disappear without automation.

That is a candidate design to evaluate on your real documents: the AI reads the document and prepares the record in your system for a person to check and release. It needs an import path a person can release and a measured extraction accuracy before it is trusted. Deterministic rules such as quantities and dates stay in your system.

Through connected data where it exists; where a carrier controls a step, the design explains the state and routes the action to the carrier or to your team. It does not promise what your systems cannot see.

Evaluate it on your own shipments.

Book a demo and we’ll walk through these candidate workflows against your transport, order and ticketing systems and the exceptions your team owns.

Book a demo callRequest pricing