# AI RFQ Review for MIM, Powder Metal and Additive Manufacturing Quotes > Source: https://netray.co/resources/ai-rfq-review-for-mim-powder-metal-and-additive-quotes > Publisher: Netray (netray.co), AI and integration engineering for ERP and manufacturing systems. > Section: Knowledge Base ## Short answer How AI helps estimators at MIM, powder metal and additive shops: read drawings and RFQs, find similar past jobs, compare processes and draft quotes for human approval. ## Category ai-automation ## Content **Intro:** AI helps MIM, powder metal and additive manufacturing estimators by reading the RFQ and drawing, extracting material, tolerance and volume requirements, finding similar past jobs and their actual costs in the ERP, comparing process routes, and drafting a quote that the estimator reviews and approves. It does not replace judgment on risk or price. These shops quote a wide mix of volumes and processes, so the value is in speed and consistency. This guide explains what the workflow does, what it should never do, and when it is not worth building. **Sections:** #### Where Estimator Time Goes in These Shops **Body:** A typical RFQ for a small complex metal part prompts the same questions: which process, what volume, which alloy, what tolerances, what secondary operations, who owns tooling. The estimator reads the drawing and specification, looks for a similar part, checks what it actually cost, guesses yield for a new geometry, and builds a spreadsheet. Much of the day goes into finding old data, not into judgment. In bureaus doing MIM, press and sinter and additive in one building, the added step is deciding which route fits at the stated volume, and that comparison is rarely written down consistently. #### What an AI Quoting Assistant Does **Body:** The assistant extracts structured requirements from the RFQ package and drawing notes, cites the source page for each value, and queries your ERP for comparable jobs by alloy, size, process and customer. It then proposes a routing and cost build using actual hours, yields and scrap from those jobs, and flags missing information such as undefined tolerances or unknown annual volume. Its output is a draft with explanations, not a final price. The estimator edits it, and any write to the ERP or quote system requires human approval. **Bullets:** - Extract alloy, density, tolerance, finish and volume from drawings and RFQ text - Retrieve similar jobs and actual yields from the ERP - Propose process route and cost build with source citations - List open questions to send back to the buyer #### Process Route Comparison **Body:** For the same print, the assistant can lay out MIM, press and sinter, machining and additive options with volume break-evens, using your own tooling costs, cycle rates and yields. This is not a substitute for engineering review; geometry may exclude a route, and tolerance capability must come from your process data. But a consistent comparison, written into the quote notes, helps buyers choose and helps you avoid quoting the wrong process. Break-evens should be shown with assumptions so the estimator can adjust them. #### Data Control and Guardrails **Body:** Many RFQs include controlled drawings, export-restricted data or customer confidential designs, so the AI should run inside your own environment, with open-weight models on your hardware or in a private cloud you control, and document permissions that mirror your existing access rules. The assistant should be read-only against the ERP by default, show the query it ran, and never send a quote to a customer on its own. Log every extraction and draft, so you can audit how a number was produced. Your obligations under ITAR, EAR or customer NDAs remain with you; the architecture should help you meet them. #### When This Is Not Worth Building **Body:** If you receive a handful of RFQs a week, run mostly repeat parts, or your ERP history is thin or inconsistent, a custom assistant will not pay back; clean up routing and actual-time capture first, since the AI is only as good as your data. A hosted instant-quote tool may also suffice for prototype additive work. The case strengthens with dozens of varied RFQs a month and an ERP with real job history. A short pilot on a sample of past RFQs, comparing the AI draft with what you actually quoted and what the job cost, shows quickly whether the data supports it. **Cta:** Send Netray a few past RFQs and the matching job actuals, and we can show what a grounded, reviewable draft quote looks like on your own data. **Faq:** #### Can AI read engineering drawings for a quote? **Answer:** It can extract many callouts such as material, tolerances, finishes and notes, especially from clean PDFs or CAD exports, but it makes mistakes on scans and dense drawings. Each extracted value should cite its source location, and the estimator confirms critical items. Treat it as a fast first reader, not an authority. #### Will AI set the price for a MIM or additive quote? **Answer:** It should draft cost and suggest a price range from your history, but a human sets the final price because margin strategy, capacity and customer relationship are judgment calls. A good setup also records the estimator's changes so the model of your costs improves over time. #### Is it safe to put customer drawings into an AI tool? **Answer:** Only if the tool runs where your data policy allows. For controlled or confidential drawings, private deployment on your own servers or a controlled cloud, with access controls and logging, avoids sending files to a third-party API. Check customer contracts and export rules before choosing a tool. ## Related Slugs - ai-quoting-aerospace-defense-manufacturers - itar-compliant-ai-tools-manufacturing - on-prem-ai-defense-contractors - manufacturing-costing-methods-comparison - ai-production-scheduling-optimization ## Search terms AI RFQ review manufacturing, AI quoting for MIM, AI estimating powder metal, AI to read engineering drawings for quotes, additive manufacturing quote automation, private AI for manufacturers, AI quote draft ERP --- Talk to an engineer: https://netray.co/contact?intent=erp_ai | Machine catalog: https://netray.co/agent/catalog.json