The RFQ is a speed problem
A request for quote, the RFQ, is where a lot of B2B manufacturing and distribution business is actually won or lost. A buyer needs a price, a quantity, and a date. They send the request and they wait.
The quote that comes back first, and is right, usually takes the order. The ones that come back two days later are quoting against a decision that has already been made.
So the RFQ is not really a paperwork problem. It is a speed problem. And speed is exactly where most shops lose, because answering an RFQ by hand is slow by design.
Where the hours actually go
Answering an RFQ looks small from the outside and is not. Someone has to read the request, which arrives as an email, a PDF, a spreadsheet, or a marked-up drawing, and no two look alike.
Then they find the parts. Then they pull the current price, the quantity on hand, and the lead time from the system of record. Then they write it all up in a reply the customer can act on.
None of that is hard. All of it is lookup. And it ties up the same skilled salespeople and application engineers you want spending their time on the quotes that genuinely need a human.
The bottleneck on a standard RFQ is not judgment. It is the time it takes a person to gather what they already have access to and put it in a reply.
What an agent does differently
An AI agent collapses that gather-and-reply loop. It reads the request however it arrives, pulls live pricing and availability straight from your own system, and returns a price, availability, and lead time in seconds instead of days.
It handles the standard requests on its own and leaves the genuinely complex ones, the custom engineering and the unusual terms, to a person.
This is not theoretical. One of our agents answers established customers' pricing and availability questions on a manufacturer's website in under ten seconds, pulling live from their own system so every answer matches what the shop would actually quote.
Another, Saugus, takes an RFQ and turns it into a buyer-ready 3D model, so the customer is looking at the thing they asked for instead of waiting on a callback.
Where the advantage actually comes from
Speed turns into win rate. When the fastest accurate quote tends to take the order, answering in seconds instead of days is not a convenience, it is a competitive position.
Availability stops being a constraint. Requests that land at night, on a weekend, or during a busy week get answered anyway, instead of sitting in an inbox until someone gets to them.
Your people get their time back. The hours that went into lookup move to the quotes that need real engineering and the customers who need a real conversation.
And the answers get more consistent. Every quote is pulled live from the same system the same way, so a customer gets current pricing, not a number from memory.
Start where it is standard
You do not hand the whole RFQ process to an agent on day one, and you should not. The advantage is biggest, and the risk smallest, on the standard, repetitive requests that are pure lookup.
Keep your people on the complex quotes. Put the agent on the ones that were only slow because a person had to stop what they were doing to look something up.
That is the honest version of what AI agents change about the RFQ. Not magic, and not a replacement for your team. Just the slow, repetitive part of winning the deal, done in seconds, so the people who close the deal can get on with it.