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AI Quote Template for Manufacturing Estimators

This AI quote template gives estimators two things: a quote document to fill and reuse, and a set of prompts that turn an RFQ into a structured list of what is known, missing and risky before you price it. It also maps the template fields to the quote fields in a typical ERP.

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AI Quote Template and Prompt Set for Manufacturing

Quotation

From: Northgate Fabrication LLC To: Halvorsen Equipment Co. Reference: RFQ-20418 Date: 2026-10-20 Valid for 30 days from the date above Prepared by: R. Alvarez

Part and scope

Part: HEC-3320 Rev C Description: Mounting bracket, 3.0 mm 5052-H32 aluminum, laser cut, bent, powder coated Quantity breaks: 50 / 250 / 1,000 Material: 5052-H32 aluminum sheet, 3.0 mm, 1,250 x 2,500 mm Lead time: 4 weeks ARO for first article, 3 weeks for repeat orders

Routing

1. Laser cut 2. Deburr 3. Press brake, 4 bends 4. Hardware insertion, 2 PEM nuts 5. Outside process: powder coat, RAL 7035 6. Final inspection and pack

Setup and run basis: Laser setup 15 min per run; brake setup 30 min per run; 0.9 min/part laser, 1.8 min/part brake.

Cost build-up (fill from your estimate)

ElementBasisPer runPer part
MaterialBlank size x price + scrap allowance
Setup laborSetup minutes x machine + labor rate
Run laborRun minutes x rate
Outside processingVendor quote or last PO + freight
Tooling / hardwarePEM, fasteners, special tooling
Inspection / packagingPer drawing requirements
Overhead and burdenPer your rate
Margin (25 %)On total cost
Quoted price

Assumptions and exclusions

Pricing assumes the drawing revision stated above, the quantities listed and standard commercial tolerances unless noted. Pricing excludes taxes, freight and any tooling or testing not listed. Prices are subject to change if the material market moves more than the agreed threshold before order.

AI prompt: structure the RFQ before you price (paste into your approved or on-prem assistant)

You are assisting a manufacturing estimator. From the RFQ text and drawing notes below, return a table with these headings: part number and revision, material and thickness, quantities, operations in routing order, outside processes, special inspection or certifications (for example material certs, first article), tolerance notes that need review, missing information to request from the customer, and risks that could change cost or lead time.

Rules: do not invent dimensions or prices. If information is not in the text, write MISSING. Ask clarifying questions as a numbered list at the end. Do not calculate the final price.

RFQ text: [paste here]

AI prompt: sanity-check the quote

Review the quote below. List (1) any cost element that looks missing for this routing, (2) setup or run times that look unusually low or high against the part description, (3) assumptions that are not stated in the quote, and (4) clarifications to send the customer. Do not change numbers. Quote: [paste here]

ERP quote field mapping

Template fieldTypical ERP quote fieldNotes
CustomerCustomer / bill-to / ship-toUse the customer master record, not free text
RFQ / referenceCustomer PO or RFQ numberKeep the customer's number for lookup
Part and revisionItem / part number and revisionCreate a prospective item if the part is new
Quantity breaksQuote lines or price breaksOne line per quantity
RoutingEstimate routing / operationsWork center, setup hours, run hours per piece
MaterialEstimate BOM / material linesInclude scrap or yield factor
Outside processingSubcontract / outside operation costPull last PO price as a reference
MarginMarkup or margin on the lineKeep policy-driven, not typed ad hoc
Lead timePromise date or lead time daysCheck against the real load

Approval

Estimator / Date
Sales manager / Date

AI is useful for reading messy RFQs and catching missing information. Do not let it invent times, prices or tolerances. Keep customer drawings and pricing inside a tool your company has approved, or run a private model on your own servers if the drawings are controlled (ITAR, export-controlled or covered by an NDA). This is a starting template, not legal advice.

Private AI for your estimators

Optional: we can show how an on-prem assistant could read RFQs and use your own quote history, with nothing leaving your network.

Optional. The tool and every export work without this. No spam.

How to use the template and prompts

Fill the fields at the top with the RFQ details, then complete the cost build-up table from your normal estimating method. Before you price, run the first prompt on the RFQ text to produce a clean list of operations, certifications and missing information. After you build the quote, run the second prompt as a second pair of eyes. The model suggests, you decide. Export the finished quote to PDF or Word for the customer, and keep the structured RFQ summary on the job record so the next estimator inherits it.

What AI is good at in quoting, and what it is not

AI is good at reading unstructured emails and drawing notes, extracting part numbers, quantities, materials and finishes, spotting missing information, and drafting the clarification email. It is not reliable at producing prices or cycle times from nothing: those come from your rates, your routings and your quote history. The reliable pattern is extract, then calculate with your own data, then review. When the model drafts numbers, show the source (similar past job, routing, rate table) or discard them.

  • Use it to structure the RFQ, not to set the price.
  • Always require a MISSING flag instead of a guess.
  • Keep a human approval step before the quote leaves the building.

Mapping to your ERP

Most ERPs hold quotes as a header (customer, dates, terms) and lines (item, quantity, price), sometimes with an estimate routing and BOM behind each line. The mapping table shows where each template field lands. The goal is to enter data once: the structured RFQ summary becomes quote lines, the routing becomes an estimate routing, and the outside process becomes a subcontract cost. Check your own system's screens and field names, because they differ by vendor and version.

Privacy and controlled data

Customer drawings and RFQs often carry NDAs and, in aerospace and defense, export-controlled technical data. Do not paste them into a public chatbot. Use a tool your company has approved, or serve an open-weight model on your own hardware, where the drawing and the model both stay inside your network. Also keep prompts and outputs in the job record so you can show later how a number was derived. Never include customer pricing from one customer in a prompt for another.

Frequently Asked Questions

Can AI price a manufacturing quote on its own?

Not reliably. It can extract requirements and spot missing information, but prices need your rates, routings, material costs and history. A sound pattern is AI extraction, your calculation, and human approval. Treat any number the model generates without a source as a guess.

What should an AI quote prompt include?

A clear role, the exact fields you want back, a rule not to invent values, a MISSING flag for unknowns, and the raw RFQ text. Ask for clarifying questions as a list. Keep the pricing step separate so you can verify it.

Is it safe to put customer drawings into an AI tool?

Only into a tool approved for that data. Public chatbots may not meet NDA or export-control obligations. Many manufacturers run an open-weight model on their own servers so drawings stay inside their network. Check your contracts and your compliance officer.

How do I get the quote into my ERP?

Use the mapping table: customer to customer master, part to item, quantities to quote lines, routing to estimate operations and outside process to subcontract cost. Many ERPs support quote import via templates or APIs, which depends on your vendor and version.

If you want the AI step to read RFQs and look up your own routings, rates and quote history without anything leaving your network, we can build that as a private assistant over your ERP and file shares.

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