How an AI Inside Sales Rep cuts RFQ turnaround from days to hours
A practical guide for CEOs/COOs in mid-market manufacturing
For most mid-market manufacturers, quoting is the bottleneck. Your estimator works through dozens of RFQs a week, each one requiring spec review, pricing lookups across the ERP and a master Excel file, and a quick call to the shop foreman when something doesn't fit a standard part number.
The result is quote turnaround measured in days, not hours. Customers go with whoever quoted first.
What's actually slow about it
A few honest observations from shops we work with:
- A senior estimator spends most of the day on retrieval and re-keying, not on the judgment work they were hired for
- Quote errors that survive review (wrong discount tier, stale surcharge, wrong revision) show up downstream as disputed invoices or margin leak
- Follow-ups fall through when the team is buried, which is most weeks
Manual quoting at most shops averages 3 to 4 business days. Shops that have systematized intake and pricing get to same-day turnaround on standard work.
What an AI Inside Sales Rep does
It works inside the systems you already have: the ERP (Epicor, JobBOSS, ProShop, SAP, whatever you run), your shared drives, your email, and the master pricing spreadsheet. It:
- Reads RFQs in the formats they actually arrive in: PDF attachments, email body specs, Excel line items, scanned drawings
- Pulls pricing from the ERP and the customer-specific tables you maintain
- Applies the customer's negotiated discount tier and terms
- Drafts the quote in your existing template
- Tracks open quotes and drafts the follow-up if the customer goes quiet
How approvals work
The first question on every call: "What if it quotes the wrong price?"
Every quote goes through human approval before it reaches a customer. Always. The reviewer sees the parsed inputs, the pricing logic that was applied, the customer history that was referenced, and the draft itself. Three configurations:
- Full review: every quote reviewed before send
- Threshold review: quotes above a dollar amount or outside normal margin bands get reviewed; routine repeat orders auto-send
- Standing approval: for known customers on standard SKUs
Most shops start at full review and move work into threshold mode as the team gets comfortable.
Week one
Here's what a typical deployment looks like:
Day 1-2: connection
- Hook into the ERP, email, and the pricing spreadsheet
- Map the product catalog and the customer-specific pricing rules
- Configure approval thresholds
Day 3-4: shadow mode
- The system drafts quotes alongside the estimator
- The estimator reviews every draft and corrects what's off
- Pricing logic and templates get tuned against real RFQ traffic
Day 5+: live
- Start with repeat customers on standard parts
- Watch the accuracy and the time-to-send
- Move more categories under the system as confidence builds
What happens after 30 days
A 180-person fabrication shop we work with had average quote turnaround of three days. After a month in production, repeat-customer quotes on standard parts went out same-day. The senior estimator stopped staying until 7 PM clearing backlog. The shop's win rate on inbound RFQs moved up in the first quarter; we won't quote a precise number because it varies week to week and depends on what the competition is doing.
Getting started
The path looks like this:
- Map the current quoting workflow (we do this with you on a discovery call)
- Connect the systems (usually a day or two)
- Set the approval rules (you stay in control)
- Start with the lowest-risk category (repeat customers, standard parts)
- Expand by category as the team builds trust
The point is not to replace the estimator. The point is to stop making the estimator do schlep work so the judgment calls actually get their time.
The bottom line
Speed wins deals in manufacturing right now. An AI Inside Sales Rep gives you that speed while keeping a human on every quote that goes out.
If you want to see how this would run on your actual RFQs and pricing, book a demo.
