Commercial print shops receive RFQs as rambling emails, scanned PDFs and photos of napkin sketches. An OCR-plus-AI intake extracts the specs into structured quote requests, turning a three-day quoting backlog into same-day turnaround for most requests.
Typical results
Same day
Quotes out the door
6 hrs
Average turnaround, was three days
92%
Specs extracted without retyping
+60%
More RFQs quoted weekly
Figures reflect typical results for this kind of automation.
The challenge
Every RFQ looked different: a paragraph of prose, a spec sheet buried in a PDF, a WhatsApp photo of a hand-drawn layout. The estimator spent 25 minutes per request deciphering and retyping specs before pricing could even start. Quotes took three days on average — and print buyers routinely gave the job to whoever answered first.
Before and after
Quote turnaround
−92%Intake typing per RFQ
−88%RFQs quoted per week
+60%The automation
We built an intake pipeline that watches the quotes inbox and pulls apart every message — body text, attached PDFs, spreadsheets, even photos of sketches. OCR plus an OpenAI extraction layer identifies quantities, dimensions, paper stock, colors, finishing, and deadlines, and writes them into a structured quote request in the CRM. When a spec is missing, the system emails the customer a polite, specific question automatically. The estimator opens a ready-to-price record, not a puzzle.
How it works
- 01
Inbox watcher
Every email to the quotes address is parsed — attachments and inline photos included.
- 02
OCR + AI read
The engine reads PDFs, spec sheets, and phone photos of hand-drawn sketches.
- 03
Spec extraction
Quantities, dimensions, stock, colors, finishing, and deadlines become structured fields.
- 04
Gap check
Missing specs trigger an automatic, polite clarification email back to the customer.
- 05
Quote-ready record
A structured quote request lands in the CRM, flagged and queued for the estimator.
Starts from
- Emailed RFQs + PDFs
- Photos of sketches
Delivers
- Structured quote request
- CRM job record
- Auto clarification emails
The impact
Average quote turnaround fell from three days to six hours, and most requests now get priced the same morning they arrive. Intake typing dropped from 25 minutes to three per RFQ, the shop quotes 60% more jobs with the same team, and win rates rose simply by answering first.
Questions about this automation
What kinds of RFQ formats can the intake read?
It reads the email body, attached PDFs and spreadsheets, and phone photos of hand-drawn layouts. OCR turns scanned pages and images into text, and an OpenAI extraction step pulls out quantities, dimensions, paper stock, colors, finishing and deadlines as structured fields on a quote request.
What happens when a request is missing a key spec?
The gap check compares the extracted fields with what the estimator needs to price the job. When something like quantity or finishing is missing, the system sends the customer a short, specific clarification email and marks the record as waiting, so the estimator only sees requests that are ready to price.
Does the estimator still check the extracted details?
Yes. The structured record lands in the CRM with the original email and files attached, so the estimator can compare any field against the source before quoting. Values the AI reads with low confidence are highlighted instead of guessed. Simple automations like this are usually live within days.