What is AI quoting software for building materials distributors?

What does AI quoting software do end to end?

Five stages, one queue. Intake routes every request into a single auditable place: a catch-all inbox for email and PDF attachments, plus WhatsApp, fax, and voice notes. Quoting.ai Supply takes voice in English, Spanish, Hebrew, and Yiddish, because that is what arrives at distributor counters in the New York metro and in Israel. Extraction splits each request into line items. Matching resolves every line against the distributor's own item file, not a generic catalog. Pricing applies that customer's price levels straight from the ERP and flags what it cannot resolve instead of guessing.

Then the two stages that make it a quoting system rather than a parsing demo: approval and write-back. The drafted quote waits in an approval inbox where a human confirms, edits, or rejects it, and the approved quote is written into the ERP as a real document, ready for the counter, will-call, or delivery.

Why are distributors buying this now?

Capacity, not novelty. Distributors we talk to describe one inside salesperson handling about 100 quotes a day and working three hours past close to clear them, and busy desks declining 30 to 50 percent of inbound RFQs because nobody has time to read them. Every declined RFQ was a customer asking to buy.

The alternative is hiring, and hiring buys capacity one salary at a time. Quoting software changes the shape of the job instead: the desk answers every RFQ, same day, with the senior estimator's pricing judgment applied across all of it, and the humans spend their hours on the calls that need judgment.

How is quoting automation different from document OCR?

OCR and generic document AI extract text from a PDF and hand back fields. That is the first step of a quote, not the quote. Distributors we talk to see a request for a 10 watt light map to 50 plus variants in their own catalog. Picking the right one takes the customer's history, the item file, stock, and that customer's price level. No amount of text extraction answers it.

The dividing line is where the tool ends. A document tool ends at extracted text someone still has to work. Quoting automation ends at an ERP-ready document: lines matched to your SKUs with unit of measure resolved, prices from your price levels, ambiguous lines flagged for a human call, and the approved quote posted to the system of record. A vendor that cannot name which ERPs it writes to today is selling the first step.

What should a buyer demand before signing?

Every vendor in this market says AI. Four demands separate working systems from demos.

• ▪A human approval step you control. Every quote should pass through an approval inbox, and review should loosen only when you decide. Quoting.ai Supply runs three modes, Assist, Guarded, and Autopilot, and every draft is reviewed until you choose otherwise.
• ▪Measured accuracy, not claimed accuracy. Quoting.ai Supply tracks Human Edit Rate, how often a human corrects a draft before it ships, and shows you the number. A vendor with no visible accuracy metric is asking for trust it has not measured.
• ▪Honest integration status, per ERP. For Quoting.ai Supply that reads: write-back live on DDI Inform and Spruce, Epicor, NetSuite, and SAP in development, ERP-light mode everywhere else. Demand the same specificity from anyone you evaluate, including us.
• ▪No zero-touch promises. Real setup is short but not invisible: for Quoting.ai Supply it is two steps, connect the inbox and upload inventory, plus an included white-glove kickoff call where a human gets you live. Anyone promising untouched automation on day one has not met a distributor's item file.