Procurement & Order Management
Request for Quotation (RFQ)
Parse customer requests for quotation into structured requirement and line-item lists for fast quoting.
The Challenge
RFQs mix prose specifications, technical tables and drawings across emails and attachments. Requirements are scattered and implicit; part references and quantities are inconsistent and need mapping to the catalogue.
Industries
Manufacturing, automotive, machinery, distribution, industrial suppliers.
Who Uses It
Sales engineers, inside sales, estimating, technical pre-sales.
BASE Schema
Requesting company — Text
RFQ reference — Text
Quotation deadline — Date
Requested positions (item, spec, qty, unit) — Table
Technical requirements — Table
Target / budget price — Number
Delivery requirement — Text
Recommended pipeline settings — Checkbox detection
OPTIONAL Validation
Requested items mapped to catalogue/SKU; quantity and spec completeness; deadline tracking; feasibility flagging.
Frequently ASked Questions
How can AI help respond to RFQs faster?
It extracts every requested item and requirement into a structured list mapped to your catalogue, so sales quotes from clean data instead of re-reading long emails.
Can document AI map customer part numbers to my catalogue?
Yes — requested parts are matched to your SKUs so pricing and availability can be applied immediately.
What is RFQ automation and why does it matter?
It is the structured capture of incoming quotation requests; faster, more complete quotes raise win rates and free sales engineers from manual transcription.
See more use cases.
Get inspired by further sample data schemas.