Customer RFQ emails and forms
Classified, extracted and linked back to source evidence for reviewer control.
Manufacturing RFQ automation
AI RFQ automation for make-to-order manufacturers
DocBeaver helps manufacturers turn RFQ emails, drawings, specifications and customer attachments into structured estimating review packs.
The workflow is designed for enquiry-heavy teams that need faster triage, clearer bid/no-bid decisions and fewer missed requirements before estimating or engineering review.
30-50%
Target reduction in RFQ administration time
Document inputs
Real documents this workflow is built around
These are the source files DocBeaver expects to map during an audit and prototype. The implementation can start with a narrow subset, then expand as extraction quality and review rules are proven.
Drawings and drawing registers
Classified, extracted and linked back to source evidence for reviewer control.
Specifications and standards
Classified, extracted and linked back to source evidence for reviewer control.
Bills of materials and part lists
Classified, extracted and linked back to source evidence for reviewer control.
Tender packs and commercial terms
Classified, extracted and linked back to source evidence for reviewer control.
Prior quotes and job records
Classified, extracted and linked back to source evidence for reviewer control.
Manual bottlenecks
Why this workflow is a strong automation candidate
Step 1
RFQs arrive with inconsistent attachments and unclear scope boundaries.
Capture RFQ emails, attachments, portal files and CRM records.
Step 2
Estimators spend time finding required documents before pricing work can begin.
Classify drawings, specifications, commercial documents and supporting evidence.
Step 3
Drawing references, deadlines, quantities and standards are re-keyed into trackers.
Extract due dates, quantities, drawing references, standards, materials and delivery requirements.
Step 4
Similar previous work is hard to find across CRM, ERP and file stores.
Detect missing drawings, unclear requirements and duplicated enquiries.
Extraction and checks
Fields extracted and validation checks performed
The automation should produce reviewable data, not a black-box answer. Every important field or exception needs a source link, confidence signal and review route.
| Extracted fields | Validation checks |
|---|---|
| Customer, contact, due date and requested delivery date | Missing drawing or specification detection |
| Part numbers, drawing references, revisions and quantities | Drawing revision and issue-date checks |
| Materials, finishes, standards and inspection requirements | Quantity and unit consistency |
| Commercial terms, assumptions, exclusions and required outputs | Requested delivery date and lead-time risk |
| Prior quote, job or product match candidates | Customer terms or unusual compliance obligations |
Workflow outputs
What the implementation should produce
DocBeaver normally starts with a controlled workflow output: summaries, exception queues, review files, dashboards or proposed system updates. Direct writes into operating systems should be added only after review rules are proven.
- RFQ triage summary
- Bid/no-bid checklist
- Estimator review pack
- CRM or Excel update proposal
- Missing-information email draft
FAQ
Common questions
Can RFQ automation read engineering drawings?
It can extract and compare useful drawing metadata, notes, tables and references where document quality allows. Engineering judgement remains with the reviewer.
Does RFQ automation generate final prices?
DocBeaver usually prepares structured inputs for estimating, quote comparison and review. Final pricing and commercial approval stay with the manufacturer.
Assess this workflow using your real documents
Start with a focused audit of document types, source systems, manual checks, exception rules and review requirements.