What Arrives in a Gear RFQ
A typical RFQ from an OEM, distributor or integrator includes a drawing or model, a gear data table, a material and heat treat specification, a quality plan or supplier quality manual, and commercial terms. Requirements hide in flag notes, general notes and referenced standards: AGMA or ISO accuracy grade, case depth and core hardness, magnetic particle or etch inspection, surface finish on the tooth flank, CoC and material cert requirements, and packaging rules. Annual volume and release schedule may be in the email, not the drawing.
A miss on any of these changes the route, and so the price.
What the AI Extracts and Checks
The assistant reads the documents and builds a structured summary with citations back to the page, so the estimator can verify in seconds.
- Module or pitch, tooth count, pressure and helix angle, face width, tooth thickness
- Accuracy grade standard and grade, and whether it is pre or post heat treat
- Material spec, heat treat process, case depth and hardness
- Special inspections, NDT, temper etch, surface finish, marking and packaging
- Quality clauses, cert requirements and flow-downs, flagged against your accepted terms
Matching Past Jobs and Drafting the Quote
With the extracted data, the AI searches your ERP for jobs with similar module, tooth count, size, material and grade, and shows actual routings, hours by operation, scrap, outside processing cost and final margin. It proposes a route and cost build-up based on those actuals and highlights where this part differs, such as a tighter grade or a new heat treat spec. The estimator edits, sets price and releases the quote.
Nothing is written into the ERP without that approval, and the query used to fetch history is shown, so the estimator can see where each number came from.
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AI Quote Template and Prompt Set for Manufacturing
A fill-in manufacturing quote plus a reusable AI prompt that turns RFQ details into a structured cost build-up, with a mapping to common ERP quote fields.
Export-Controlled and Customer-Confidential Drawings
Many gear and power transmission drawings go to defense, aerospace and energy customers and carry ITAR, EAR or customer confidentiality markings. Sending those drawings to a public AI service is a compliance risk your customer contract may prohibit. The workable approach is to run open-weight models on hardware in your facility or private cloud, with document-level permissions and logs, so you can meet your own obligations.
Netray does not hold certifications on your behalf; the architecture simply lets you keep the data inside your boundary and show how it was handled.
When This Is Not Worth It
If you get a few RFQs a week, your estimator knows the families by heart and your drawings are mostly repeat work, a good ERP template or a spreadsheet may be enough. AI pays back when RFQ volume is high, drawings are varied, past job data is scattered and estimators spend more time reading and searching than thinking. It also needs reasonably clean history: if actual hours and scrap are not booked consistently, the AI will faithfully reproduce the noise.
Start with one part family to test value before a wider rollout.
Frequently asked questions
Can AI read a gear drawing data table?
Often yes, from clean PDFs and many scans, especially when the table is standard. Results should be treated as a draft with citations and verified by the estimator. Poor scans, handwritten notes and unusual layouts need human review. The goal is to save reading time, not to remove the check.
Is it safe to put customer drawings into AI tools?
Only if the tool runs where your contract allows. Public cloud AI services may violate ITAR, EAR or confidentiality terms. Running models on your own hardware or private cloud, with access controls and logs, lets you keep drawings inside your boundary. Check your customer agreements.
Will AI set my gear prices?
It should not. It drafts a route and cost from your history for an estimator to review. Price depends on capacity, customer, risk and strategy, which are human decisions. The AI's role is to make the evidence faster to gather and easier to trust.
Send Netray a redacted gear RFQ and a few past jobs, and see a sourced extraction and draft route produced privately.