Agent StoreSalesRequest for Quote Processing
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Manufacturing RFQ Response Agent

SalesRequest for Quote Processing

Analyzes incoming manufacturing RFQs against plant capacity, material costs, and historical pricing to generate accurate, timely customer quotes.

4
Process steps
5
Integrations
3
Data inputs

Sales and estimating teams at custom manufacturing and fabrication shops receive detailed RFQs specifying part drawings, quantities, and delivery timelines, and must manually estimate material cost, machine time, labor, and available production capacity before quoting a price, a process that can take days and often produces inconsistent pricing depending on which estimator handles the request

Slow or inconsistent quotes lose competitive bids to shops that can respond faster with reliable pricing

This agent parses incoming RFQ specifications, calculates estimated material and machining/production costs using current cost data and historical job records for similar parts, and checks the request against current plant capacity and lead time before generating a draft quote

It flags RFQs that would require capacity beyond what's available in the requested timeframe so sales can negotiate delivery expectations upfront

The agent extracts part specifications, quantities, and required delivery dates from incoming RFQ documents, then estimates material cost from current supplier pricing and production time from historical job records and standard routing data for similar parts. It cross-references the estimated production time against current plant capacity data to confirm the requested delivery date is achievable, and applies the company's margin and pricing rules to generate a draft quote. Quotes are routed to the estimator or sales rep for review and adjustment before being sent to the customer.

1

RFQ Parsing

  • Extract part specifications, drawings, and quantities from the RFQ
  • Identify required delivery date and any special requirements
  • Match the request to similar historical jobs for reference pricing
  • Flag any specification requiring engineering review before quoting
Outcome: RFQ requirements are fully extracted and matched against historical job data for reference.
2

Cost Estimation

  • Calculate material cost from current supplier pricing
  • Estimate machine and labor time from routing and historical cycle data
  • Apply overhead allocation and standard margin rules
  • Compile a total estimated cost and suggested quote price
Outcome: An accurate, data-driven cost estimate and suggested price are generated for the RFQ.
3

Capacity Feasibility Check

  • Check estimated production time against current plant capacity
  • Verify the requested delivery date is achievable given the schedule
  • Flag RFQs requiring capacity beyond what's currently available
  • Suggest an achievable alternate delivery date where needed
Outcome: Delivery feasibility is confirmed or flagged before a commitment is made to the customer.
4

Quote Drafting & Routing

  • Generate a formatted draft quote with pricing and delivery terms
  • Route the draft to the estimator or sales rep for review
  • Track quote status and win/loss outcome once submitted
  • Feed actual job cost data back into the historical reference dataset
Outcome: A ready-to-send, accurate quote is produced quickly, with outcomes tracked to improve future estimates.
CRM/quoting system (e.g., Salesforce, Zo
ERP job costing and routing data
MES (Manufacturing Execution System) cap
Supplier pricing/procurement system
Email for quote delivery