Quick Overview
AI freight quoting software helps teams interpret enquiries, retrieve relevant pricing information and prepare customer offers. A dependable workflow combines AI assistance with approved rate sources, deterministic pricing calculations and human review. Evaluate how the system handles missing details, conflicting rates and customer commitments before allowing quotes to be sent.
What can AI freight quoting software automate?
AI can assist with the interpretation of unstructured information. Pricing rules and calculations should remain explicit and testable. A quote containing all the expected fields can still be wrong if it uses an inapplicable rate or overlooks a condition.
| Input | AI assistance to evaluate | Human control | Intended output |
|---|---|---|---|
| Customer enquiry | Classify the request and extract shipment details | Confirm ambiguous locations, cargo and dates | Structured quote request |
| Supplier rate file | Suggest fields, charge mappings and applicable conditions | Resolve extraction exceptions before publication | Reviewed rate record |
| Candidate rates | Organize comparable options and highlight missing costs | Approve the selected service and assumptions | Cost comparison |
| Pricing rules | Assist with retrieving the relevant customer policy | Approve exceptions to margin or markup rules | Reviewed sell price |
| Quote draft | Populate the customer document from approved inputs | Approve the offer before sending | Customer-ready quote |
These are evaluation areas. Confirm which functions are available in the proposed product and configuration.
Start with a complete shipment request
Classify whether the customer wants a new quote, a revision or an explanation of an existing offer. Match the request to an existing reference before creating another record.
Extract origin, destination, movement scope, mode, cargo details, equipment and required dates where present. Highlight missing information instead of filling it with plausible assumptions.
For example, “Barcelona delivery” does not establish whether the request ends at the port, airport or an inland address. The quoting workflow should obtain clarification before selecting local charges.
Use approved rates and comparable service scopes
A retrieved rate is a candidate, not an automatically valid choice. Check its supplier, version, validity, mode, equipment, commodity and customer restrictions.
Compare total known costs for the same service scope. Call a calculation “landed cost” only when all relevant elements, including applicable duties and taxes, are actually included. Otherwise identify the total as an estimated freight cost and list missing items.
Charge normalization should preserve the original supplier description and calculation basis. Similar names do not prove that two charges cover the same service.
The detailed preparation process belongs in the freight rate-sheet automation guide.
Apply margin and markup rules explicitly
Margin and markup use different denominators. Store the selected method, its input costs and any minimum or approval threshold in defined pricing rules.
Use a calculation engine for arithmetic rather than accepting an unexplained number generated by a language model. The reviewer should be able to trace the sell price to the approved costs and policy.
If a proposed offer falls outside the permitted range, route it for authorization. Keep the reason for the exception with the approved version.
Handle uncertain or conflicting rates
When two sources disagree, establish whether they describe different dates, services or customer conditions. Do not automatically choose the cheaper record or assume the newest file replaces every previous term.
A useful exception record identifies the conflicting fields, source references and decision needed. The owner can request clarification, select a verified alternative or hold the quote until the issue is resolved.
An uncertain price should remain visibly uncertain through document preparation. It should not become a confirmed customer charge merely because a PDF has been generated.
Approve the offer and preserve its history
Before sending, review the shipment scope, applicable charges, exclusions, quote expiry and booking conditions. Confirm the customer recipient and current document version.
Keep source references, corrections, pricing overrides, approvals and the final sent version in the workflow history. Verify that this evidence can be retrieved during a demonstration.
Customer acceptance is a commercial event. It does not by itself establish carrier space, equipment availability or booking confirmation.
See quote management for the broader product workflow.
Example: an enquiry with incomplete delivery details
This example is hypothetical.
A customer requests an ocean quote from Shanghai to Barcelona and mentions delivery without providing an address. AI extracts the ports and cargo details but flags the destination scope as incomplete.
The team requests the address, confirms the required equipment and selects rates covering the same movement. A destination charge remains unclear, so the quote stays in review until the supplier confirms it.
The approved offer then includes the selected service, complete known charges, explicit exclusions and expiry. The reviewer approves the customer document before release.
The value comes from organizing the work and exposing unanswered questions, not from guessing the missing information.
How to choose the best AI freight quoting software for your team
Test the same examples with each provider: an incomplete enquiry, an ambiguous surcharge, an expired rate and a quote requiring approval.
Measure time from a complete request to an approved offer, correction frequency and unresolved cases. Include review time. Confirm supported sources, permissions, integration costs and whether the demonstrated controls are included.
For the wider operational process, see freight pricing desk automation. For related use cases, explore AI for freight forwarders.