Why Quotation Automation Matters More than it did Two Years Ago?
For most of the last decade, quoting meant a sales rep manually paging through rate sheets and tariff tables, cross-referencing surcharges by hand, and formatting a document line by line, work that scaled with headcount, not with how many quotes actually needed sending. That's changed. The document AI market has shifted decisively toward large language models that read pricing structures the way a rate analyst would, understanding which tariff applies, what surcharges stack, and how a lane should actually be priced, not just returning the first number that matches a search.
The practical result: a quote that used to take twenty or thirty minutes of manual digging now generates in a fraction of that time, not because the underlying rates got simpler, but because the system resolves rate selection and validation on its own before it needs to ask a human.