How long does onboarding take, and what do you need from us to get started?
Key Takeaways
Updated October 28, 2026
Wilson's onboarding time depends on the freight workflow, system access, and setup work the company needs. Your AI logistics coordinator needs sample orders, approved carriers, operating rules, approval limits, and contacts. A straightforward starting scope differs from a custom ERP project. Agree on the actual plan before relying on a launch date.
- Choose the first freight task before planning the rollout.
- Bring a normal shipment example and one common exception.
- Identify who owns order data and system access.
- Supply the carrier list, contacts, and approval rules.
- Test the workflow through its agreed endpoint.
- Assign a person to resolve open setup questions.
Wilson, by Cartage, is an AI logistics employee for manufacturers and distributors. You onboard Wilson around the freight work you need completed. That work can include quoting, booking, tracking, documents, invoice auditing, and payments. The company supplies its operating knowledge. The setup should turn that knowledge into an understandable workflow with clear responsibilities.
What determines how long onboarding takes?
The starting scope and its dependencies determine the onboarding plan. Your AI logistics coordinator may begin with an agreed order input and existing carrier contacts. A custom interface or unclear operating rule adds a different kind of work. The company should identify those dependencies before requesting a reliable date. No single duration applies to every customer environment.
| Setup area | What the company should provide | Why it matters to the plan |
|---|---|---|
| Starting workflow | The first task and intended endpoint | Defines what must work before the scope is ready |
| Order input | A representative email, export, spreadsheet, or system record | Shows the information available for freight coordination |
| Carrier setup | Approved providers, contacts, and relevant account details | Defines who Wilson may contact and book |
| Operating rules | Service needs, selection rules, and approval limits | Establishes permitted actions and human decisions |
| System access | The relevant access owner and proposed method | Identifies technical dependencies |
| Evaluation | Normal and exception examples | Shows whether the proposed workflow meets the need |
| Ongoing ownership | Contacts for decisions and later changes | Keeps unresolved work from losing its owner |
Separate effort from elapsed time
A task can require little effort yet wait on another team's decision. Your AI logistics employee setup may need an access approval or a carrier contact that operations cannot supply alone. The plan should identify those dependencies. Otherwise, a simple workflow can appear difficult when the real issue is an unanswered request. Ask who owns each pending item and what information they need.
Consider an illustrative manufacturer of industrial pumps. Its logistics team knows how it ships finished products, but IT manages the order export. The AI logistics coordinator setup needs both groups. Operations can explain the shipment requirement while IT confirms the data method. A useful plan names those responsibilities. This example does not claim a customer implementation duration or a guaranteed rollout result.
Distinguish a normal starting task from custom work
The first scope should identify any customer-specific technical work. Your AI logistics employee may use an agreed file or email input while a more detailed connection is considered. A custom integration should have its own explanation. The buyer should understand what is available for the starting task and what remains separate. Do not assume that every later requirement belongs in the same launch promise.
The pump manufacturer might start with released orders from one site. Its AI logistics coordinator can then be evaluated through that operating flow. Another site may use different contacts or service rules. The company should keep those differences visible. Starting with one scope does not prove that the whole operation is already configured. Expansion should follow the requirements of the additional work.
Agree on what ready means
Readiness should describe a working freight handoff, rather than the completion of an introductory meeting. Your AI logistics employee setup needs an agreed input, permitted action, and relevant endpoint. The company should know what the first scope includes. A connected account can be necessary without being sufficient. The operational test should show whether the intended task can proceed with the supplied information.
For the pump manufacturer, readiness might involve turning a released shipment into an accepted carrier booking under the agreed rules. Its AI logistics coordinator evaluation should inspect that result. The business should separately identify later tracking or return-update requirements. This is an example of scope definition, not a claim that every customer receives the same onboarding sequence or acceptance process.
What should we prepare before the first setup discussion?
Prepare a small set of real operating examples and the rules used to handle them. Your AI logistics coordinator needs to understand what the company wants done and which information supports the task. Start with material the team already uses. The aim is a usable playbook, rather than a perfect manual covering every possible event.
Bring a representative order
Choose an authorized example that reflects ordinary freight work. Your AI logistics employee setup should include the actual kinds of references, addresses, dates, and freight details the workflow will receive. Explain the meaning of each important field. A simplified example can hide the problem the business wants to solve. The setup discussion should expose that problem early.
The pump manufacturer can bring a released order and the email its coordinator normally sends to a carrier. Its AI logistics coordinator discussion can then compare the two. The team may discover that the email contains important details missing from the order export. That is useful information. The business can identify where those details come from before treating the input as a complete shipping instruction.
Bring the current carrier process
The carrier list should identify the providers the company has approved for the relevant work. Your AI logistics employee also needs usable contacts and the applicable operating instructions. A provider appearing in a connection catalog is not the same as customer approval to place freight. The company should explain its own carrier rules. Include the relationships that matter to the starting workflow.
The pump manufacturer may have different approved providers for different services. Its AI logistics coordinator setup should preserve that distinction. The team should explain who can approve an alternative and what happens when the normal option is unavailable. Avoid leaving that decision hidden in one employee's memory. The setup needs a clear instruction for the point where ordinary coordination becomes a human choice.
Bring the rules behind everyday decisions
Explain how the team decides which quote or service it can accept. Your AI logistics employee needs those rules to work within the company's limits. A previous booking shows what happened once. The playbook should explain whether that decision represents normal policy. The buyer should separate a repeatable rule from an unusual exception approved for one customer or load.
Ask the experienced coordinator to describe one easy shipment and one difficult shipment. Your AI logistics coordinator setup can use that comparison to identify the condition that changes the next action. The issue may be a receiving window, an unavailable carrier, or a missing detail. Record the decision and its owner. Those facts are more useful than a broad instruction to choose the best option.
Identify the contact for missing facts
The setup should name the person who can answer each important question. Your AI logistics employee may need readiness information from the warehouse and a delivery requirement from customer service. The company should explain who supplies those facts. One general project contact may not know every operating detail. Named owners make the handoff clearer for both the setup and the ongoing workflow.
The pump manufacturer can keep a short list of information owners beside its example order. Its AI logistics coordinator may need to know which team confirms the packed weight. A different contact may approve a changed service. The list should reflect the actual work. It should not become an assumed guarantee that every question will be answered within a fixed time.
Who should take part in onboarding?
Operations should own the freight instructions, while the relevant system and business owners support their parts of the setup. Your AI logistics coordinator needs access to the right knowledge, rather than a large meeting for every question. Identify a primary operating contact and the people who can resolve specific dependencies. Their roles should match the starting scope.
Give operations ownership of the playbook
Operations should explain how the freight task works and what a good result looks like. Your AI logistics employee needs the rules used for carrier selection, follow-up, and exceptions. The setup team cannot infer every customer promise from a shipment row. The business should identify the person who can approve the operating instructions. That owner should also resolve conflicting guidance from different sites or employees.
The pump manufacturer's logistics leader might approve the carrier rules while a coordinator explains the daily workflow. Its AI logistics coordinator setup benefits from both views. The leader can set the boundary, and the coordinator can show where information is usually missing. The company should resolve any disagreement before treating either account as the approved process. Otherwise, the setup can encode an unclear expectation.
Involve IT where the scope requires it
IT should review the proposed system access and data path. Your AI logistics employee may work from email, files, or an ERP-related flow. The relevant technical owner should explain what the environment supports. That review differs from owning the freight decision. IT can confirm an export or access method while operations defines what should happen after the data arrives.
The company should also identify who maintains the connection or input after setup. Your AI logistics coordinator workflow can depend on a recurring export or a connected account. The team should know who handles a changed layout or access problem. This article does not assume a particular support arrangement or recovery commitment. Those responsibilities should be confirmed for the proposed customer setup.
Include finance when payment work is in scope
Finance should explain the records and decisions required for the agreed payment workflow. Your AI logistics employee handles freight audit and payment coordination, but the company still needs clear financial responsibilities. Finance should identify the evidence it uses and the people authorized to decide exceptions. It should also review the applicable commercial arrangement. Do not treat a general product description as a substitute for that review.
The pump manufacturer may want to inspect invoice reconciliation after the booking and tracking work is established. Its AI logistics coordinator plan should identify that sequence as a proposed scope choice. The team should confirm what is included in its actual arrangement. An operating evaluation does not establish a standard free trial, contract term, or universal financial control. Those conditions need separate confirmation.
Name an owner for the overall decision
A business owner should decide whether the starting scope meets the intended need. Your AI logistics employee evaluation may involve several teams, but somebody needs to reconcile their findings. That owner should keep the original objective clear. The objective might be reducing a particular kind of manual follow-up, rather than replacing every system at once. The decision should reflect the actual operating result.
The owner should also keep unresolved questions visible. Your AI logistics coordinator setup may require another input, approval rule, or technical decision. A named owner can decide whether that issue blocks the starting scope or belongs in later work. That is a business judgment. The setup should make the dependency understandable rather than bury it inside an optimistic launch date.
How do we choose a useful starting workflow?
Choose a repeatable freight task with clear inputs, rules, and a result the team can inspect. Your AI logistics coordinator should begin with a scope that exposes the relevant operating work. Narrow does not mean artificial. The task should represent a real problem the company wants solved, including the common exception that makes manual coordination difficult.
Start with a concrete endpoint
The endpoint should describe completed work, such as carrier acceptance or receipt of the required delivery evidence. Your AI logistics employee evaluation should not stop at a message sent unless sending that message is the actual agreed task. The team should know what result it expects. A precise endpoint helps the provider explain what the proposed setup will and will not complete.
For the pump manufacturer, a useful starting task may be quoting and booking a released outbound shipment. Its AI logistics coordinator needs the service requirement, approved carrier rules, and approval contact. The company can follow the task through the carrier response. It should also inspect any manual work left for the team. That gives the evaluation a practical basis without claiming an invented efficiency benchmark.
Use a common exception
A common exception shows whether the setup fits the work beyond the easy path. Your AI logistics employee might need to handle a missing answer, incomplete order, or changed ready date. Choose the case that causes recurring work for the team. The demonstration should show what happens next. It should also identify the point where a person makes a decision.
The pump manufacturer can use a carrier that does not answer the pickup question in the example. Its AI logistics coordinator should follow the configured process for that situation. The buyer should ask what is set up, what the provider demonstrates, and what the customer still does. This is a test method. It does not promise a specific retry schedule or automatic replacement behavior for every account.
Avoid expanding the first scope by accident
New requirements should be reviewed rather than silently added to the launch expectation. Your AI logistics employee setup may begin with one carrier workflow and later reveal a separate ERP update need. Both can matter, but they may require different work. The company should identify which requirement belongs in the first scope. That keeps the implementation discussion tied to an agreed objective.
Read how email and files can support a starting freight workflow when deciding the input method. Your AI logistics coordinator may not need a full API project for every initial task. The proposed arrangement still needs accurate information and a clear change path. A simpler input should reduce unnecessary complexity without hiding the operating work that remains.
Plan expansion from observed work
Expansion should follow a review of the additional task and its dependencies. Your AI logistics employee may encounter different rules at another site or in another mode. The company should identify those differences before assuming the initial setup applies unchanged. A working first scope is useful evidence for that scope. It is not proof of universal coverage across the whole organization.
The pump manufacturer may later add another warehouse with different collection requirements. Its AI logistics coordinator plan should include the relevant contacts and service instructions. The team can reuse approved knowledge where it fits. It should still review the differences. This makes expansion an operating decision rather than a general promise that every later workflow requires no additional setup.
What should we test before the starting workflow goes live?
Test the agreed task from its real input through the relevant result and human handoff. Your AI logistics coordinator evaluation should include a normal case and an important exception. Inspect what the next person sees. The business needs to know whether the workflow supports the actual freight decision, rather than merely demonstrating that an account or connection exists.
Check the starting information
The test should show how the shipment becomes ready for action. Your AI logistics employee needs a clear instruction tied to the relevant movement. The team should inspect the references, freight details, dates, and service requirement. If a fact is missing, identify the question and owner. The result should not depend on a person quietly correcting the record without that work being acknowledged.
The pump manufacturer can compare the test input with its normal order preparation. Its AI logistics coordinator setup should make any extra preparation visible. A demonstration built from a perfect record may hide recurring work. Record the actual steps the business needs to supply the information. That provides a more useful operating picture than assuming every future order will arrive in the same clean form.
Check the approved action
The test should show how the next action follows the company's rules. Your AI logistics employee may request a quote, seek clarification, or wait for a decision. The company should inspect the reason that applies. A rule should connect the shipment condition to the permitted action. A general statement about retaining control is less useful than a concrete example of that boundary.
Read how approval rules guide Wilson's freight work when preparing the exception case. Your AI logistics coordinator evaluation should show what information reaches the approver. The team should know what continues while that decision is pending. Confirm the actual behavior proposed for the setup instead of inferring every control from a general approval capability.
Check the carrier result
The business should inspect evidence of the relevant carrier response. Your AI logistics employee may obtain an accepted booking, a revised estimate, or a document. Those results differ from an unanswered message or an internally selected option. The test should preserve that distinction. Ask the provider to show the information that supports its description of the completed task.
For the pump manufacturer, a booking evaluation should identify what the carrier has accepted. Its AI logistics coordinator may still need a clarification before the result is usable. The team should record that remaining question. An honest incomplete result is more useful than treating a partial answer as completion. It shows where the proposed operating process still needs work or a decision.
Check the human handoff
An escalation should give the next person a clear question and the relevant facts. Your AI logistics employee may reach a limit that requires customer judgment. The person receiving that request should understand the shipment, unresolved issue, and decision needed. A vague alert can create another investigation. Inspect the handoff as part of the test, rather than treating its existence as sufficient.
The company should also know who acts when the usual contact is unavailable. Your AI logistics coordinator arrangement needs that responsibility to be agreed for the workflow. This is a planning requirement, not a claim that every account includes a particular fallback mechanism or support response time. Ask the setup team to explain the proposed process for the people who will actually use it.
What happens after the first workflow is running?
The team should review the operating result, resolve open questions, and maintain the playbook. Your AI logistics coordinator needs current contacts, rules, and shipment instructions. A useful review looks at completed freight work and the effort still required from people. It should distinguish a setup problem from a new requirement or an exception that remains a human decision.
Review the result against the starting objective
The company should return to the problem it wanted the workflow to solve. Your AI logistics employee may complete carrier follow-up while the team still prepares the same order input. That distinction belongs in the review. Record what changed and what remained. Do not infer savings, staffing effects, or delivery improvements without the relevant evidence from comparable work.
The pump manufacturer might record the number of unresolved carrier questions and the manual steps left in its selected task. Its AI logistics coordinator review should use consistent definitions. The point is to understand the operating result. This article supplies no benchmark or promised outcome. The team should collect its own evidence before making wider claims about the value of the arrangement.
Maintain instructions as the business changes
An operating owner should review changes to carriers, contacts, service requirements, or approval limits. Your AI logistics employee needs updated instructions when those facts change. The company should agree on the method for maintaining its setup. Do not assume that every email automatically changes the standing playbook. A one-time exception and a new rule should be distinguished.
The pump manufacturer may approve a special arrangement for one customer shipment. Its AI logistics coordinator should receive the relevant instruction for that work. The operating owner should separately decide whether the arrangement becomes standard. That distinction helps the human team maintain a consistent process. Confirm how the proposed setup handles changes before relying on it for repeated freight decisions.
Keep commercial questions separate from operating readiness
A working demonstration does not define the customer's contract or charges. Your AI logistics employee proposal should have a clear commercial scope alongside the operating scope. Confirm any setup work, applicable fees, support arrangement, and contractual conditions directly with Cartage. This article does not establish a free trial, standard pilot, cancellation right, or fixed implementation price.
The company can still prepare its operating examples while those discussions continue. Your AI logistics coordinator onboarding plan should identify which facts are confirmed and which remain open. A clear plan gives each unresolved item an owner. It also prevents a technical demonstration from being mistaken for a commitment about commercial terms. Both parts need to be understood before the business relies on the arrangement.
Keep a clear record of open setup decisions
The company should maintain a short list of questions that still need an answer. Your AI logistics employee setup may depend on a carrier contact, a release rule, or a decision about return information. Give each item an owner and describe why it matters. The list should distinguish a launch dependency from a useful later enhancement. That helps the team focus without pretending every unresolved question has the same effect.
For the pump manufacturer, a missing warehouse contact may affect the first pickup workflow. Its AI logistics coordinator plan should identify the person who can supply that contact. A later reporting preference may have a different priority. Operations and the setup team should agree on those distinctions. The plan should explain their reasoning in ordinary language so the business owner understands what is ready and what is still being decided.
The same record can support the review before live use. Your AI logistics employee arrangement should not depend on assumptions that nobody has accepted. Revisit the relevant open items and confirm the current instruction. Keep any remaining limitation visible to the people who will operate the workflow. This is a practical preparation step, rather than a claim that every customer follows a fixed onboarding schedule.
FAQs
How long does onboarding take, and what do you need from us to get started?
Timing depends on the scope and setup dependencies. Your AI logistics coordinator needs sample orders, approved carriers, contacts, operating rules, approval limits, and the relevant access. Agree on the actual plan with Cartage.
Do we need to write a complete SOP before starting?
You need clear instructions for the selected workflow. Your AI logistics employee setup can begin with existing operating examples and the rules behind them. Identify common exceptions and their owners.
Does every rollout require a full ERP API project?
No. Your AI logistics coordinator can work from an agreed file, spreadsheet, or email input where it fits the task. The actual method depends on the environment and scope.
Does an onboarding evaluation mean a free trial is included?
No. A test describes how you inspect the proposed workflow. Your AI logistics employee arrangement still needs its commercial terms confirmed directly with Cartage.