AI for Swiss and Screw Machine Shop Quoting

The Problem: Quoting Is a Search Task

Most of an estimator's time on a turned-parts RFQ goes to reading and searching, not arithmetic. Read the drawing for material, diameters, tolerances, threads, cross holes, finishes and notes. Remember or look up a similar part.

Open its old job, check actual times, check what secondary operations it needed, and adjust. That search depends on memory and on how well past jobs are recorded. When the person with the memory is busy, on vacation, or retired, quotes slow down or get less accurate.

AI is well suited to this kind of retrieval over drawings and ERP history.

What the Agent Does Step by Step

A private quoting agent works through the same steps as a senior estimator, citing sources at each one, so the human can check the work quickly.

• Extract material, bar size, tolerances, features, secondary operations, quantities and delivery from the drawing and RFQ email
• Find similar past parts by material, diameter, length and feature set across ERP jobs and quotes
• Pull actual cycle time, setup hours, bars issued, scrap and outside processing cost from those jobs
• Flag risk items such as tight runout, thread whirling, unusual materials or documentation requirements
• Draft quantity-break pricing with the cost basis shown for each line

What Must Stay With the Estimator

Pricing strategy, risk judgment and customer relationships are human decisions. So is acceptance of terms, any export-control or quality clause, and the final send. The agent should be read-only against the ERP, should show the retrieval it used, and should never email a customer or write a quote record without approval.

Treat its output the way you treat a junior estimator's draft: useful and fast, but checked. Track how often estimators change the draft and why; those corrections show where the data or the logic needs work.

Data Readiness and Privacy

AI quoting is only as good as your history. If past jobs lack actual hours, if part numbers do not describe the part, or if quotes live in scattered spreadsheets, the first step is making that history searchable, which is often valuable on its own. Customer drawings can be confidential or export controlled, and some turned-parts shops supply defense or medical customers.

Running the models on your own hardware or private cloud, with document-level permissions, keeps drawings inside your boundary, so you meet your obligations rather than uploading prints to a public service.

When AI Quoting Is Not Worth It

If you quote fewer than perhaps ten new parts a week, if most of your work is repeat parts with fixed prices, or if your history is too thin to compare against, the payback is weak. A well-built quote worksheet, a calibration table for cycle times and a shared folder of past quotes may do more for less. Turn to AI when the volume of RFQs, the number of estimators, or the delay between request and quote is clearly costing you work, and start with a small pilot on one product family to measure whether estimator time and quote accuracy really improve.