What is RFQ automation?
RFQ automation is the use of software to turn an incoming request for quotation into a priced, margin-checked quote without manual re-typing. A buyer sends an RFQ — usually as an email, spreadsheet or PDF — listing products, quantities and delivery terms. An RFQ automation system reads that request, identifies the customer, matches each requested line to a real product in the seller's catalogue, retrieves current vendor or list prices for those products, assembles a cost sheet including duty, freight and other landed costs, applies the seller's margin rules, and produces a draft quote in the customer's currency. The draft is then reviewed and approved by a person before it reaches the customer. RFQ automation differs from configure-price-quote (CPQ) software, which starts from a configured product a salesperson selects; RFQ automation starts from unstructured inbound text written by the buyer, so the hard part is interpretation and matching rather than configuration.
The stages of an RFQ automation pipeline
These are the stages implemented in Quote AI, the RFQ automation product built by WorkAgents AI. Every stage produces a record; nothing is discarded silently.
1. Parse the RFQ
The inbound message is read and broken into structured line items — product text, quantity, unit, requested delivery. The original product text the buyer wrote is stored unchanged, so that a later match can always be traced back to what was actually asked for.
2. Resolve the customer
The sender is matched to an existing customer account. A recognised company writing from an unfamiliar email address is flagged rather than assumed, because that pattern is both a common data-quality problem and a common impersonation route.
3. Match products
Each parsed line is matched against the product master with a confidence score. Lines that cannot be matched confidently are marked for a human instead of being guessed.
4. Procure vendor costs
Current buying prices are retrieved from vendor price records, filtered by validity. Where costs are missing, the run parks and waits rather than inventing a price.
5. Draft the quote
A cost sheet is assembled — landed cost, currency conversion, taxes — margin rules are checked, and a quote is drafted in the customer's currency, versioned so every revision is a snapshot rather than an overwrite.
6. Human review
The draft stops at an approval gate. An approver accepts, edits or rejects it. Only then is a quote issued. See how human-in-the-loop approval works.
What RFQ automation is not
| RFQ automation | CPQ | RFP response software | |
|---|---|---|---|
| Starts from | Unstructured inbound buyer request | A configuration a seller selects | A long questionnaire or tender document |
| Core difficulty | Interpreting and matching what was asked for | Valid product configuration and rules | Assembling written answers and evidence |
| Priced from | Live vendor / landed cost | Price book and discount rules | Usually out of scope |
| Typical output | A quote with a cost sheet behind it | A configured, priced order | A document submission |
Where RFQ automation pays off
It is worth automating when RFQs arrive as free text, the catalogue is large enough that matching is real work, and prices come from vendors rather than a fixed price book. Distributors, traders, industrial manufacturers and pharmaceutical exporters fit this shape. Pharma is the sharpest case: the same molecule at a different strength, form or pack size is a different sellable product, so a text match on the product name is not sufficient — matching has to be salt, strength, form and pack aware to be correct.
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