Proposed workflowFreight sales · Operations

Turn an RFQ into a lane table

Extract lanes and requirements while leaving missing units, dates and volumes visibly unresolved.

Added 2026-10-14 · Reviewed 2026-10-14

Untested idea · The sample is fictional and does not document an actual deployment or model test.

The task

RFQs mix lane details, assumptions and missing requirements in prose. A neat spreadsheet can conceal gaps that matter for quoting.

How to get started

Paste the instructions followed by the RFQ. Request one row per lane.
Copy the tab-separated output into your spreadsheet.
Compare each cell to the RFQ; resolve the missing fields before quoting.

Expected result

A lane table plus a separate missing-information checklist. No calculated or recommended rate.

Instructions to copy

Extract only facts stated in this RFQ. Return TSV with columns: Origin, Destination, Equipment, Weight as stated, Frequency, Pickup requirement, Missing details, Source reference. One row per lane. Keep units exactly as written; never infer pounds, kilograms, frequency, complete addresses or appointment dates. Use Unknown for omitted values. Then list questions to resolve before quoting. Do not calculate a rate, select a carrier or make commitments.

RFQ:

Try the fictional sample

Download input ↓

Illustrative input and output. These are not recorded model results.

Sample input

[R1] Please quote Dallas TX to Chicago IL, 53-foot dry van, 20,000 lbs, two loads per week, Monday pickups.
[R2] Also Memphis TN to Atlanta GA, dry van, weight 18,000 (unit not given). Volume and pickup schedule TBD.

Illustrative output

Origin	Destination	Equipment	Weight as stated	Frequency	Pickup requirement	Missing details	Source reference
Dallas TX	Chicago IL	53-foot dry van	20,000 lbs	2 loads/week	Monday	Full addresses; start date; commodity; delivery requirements	R1
Memphis TN	Atlanta GA	dry van	18,000 — unit unknown	Unknown	Unknown	Weight unit; trailer length; frequency; schedule; addresses; commodity	R2

Before quoting: confirm all missing details with the customer.

Human review required

Check origin/destination specificity, equipment, weights and their units, appointment dates and frequency.
Preserve uncertain units instead of guessing; a city is not a complete pickup address.
Confirm volume and requirements with the customer before making any pricing commitment.

Evidence & limitations

Proposed workflow; no real-data accuracy benchmark or documented model execution.
The fictional example is an illustration of the expected structure.
OCR errors, merged cells and large attachments may require manual review.