A step-by-step approach to speeding up RFQ response without cutting corners on accuracy.
Key takeaways
In competitive bidding, the shop that responds first often has an edge before price is even compared, because customers frequently move forward with whoever answers quickly and clearly. Slow quote turnaround loses bids you'd otherwise win.
AI can draft a quote from an incoming RFQ using your historical job and pricing data far faster than an estimator working from scratch, without skipping the review that keeps it accurate.
The quality of an AI-drafted quote depends entirely on the historical data behind it: past jobs, actual costs, margin targets. Shops that organise this data properly before piloting see dramatically better first drafts than those that don't.
This is worth investing real time in upfront, since a few days spent structuring past job data pays off in every quote that follows.
An AI-drafted quote should always pass through an estimator who checks pricing assumptions, material specs, and lead time before it goes to a customer. This isn't a formality; it's what catches the edge cases a historical average can't anticipate.
The time saved isn't in skipping this review, it's in not having to build the draft from a blank spreadsheet first.
Turnaround time is the obvious metric, but win rate matters more: a faster quote that's also accurate wins more bids than a faster quote that has to be corrected after the fact and damages trust.
Track both for a quarter after rollout. Most shops see turnaround improve first, with win rate following as the process settles in.
A 30-minute call is enough to tell you whether AI pays for itself here.
