# AI Quoting for Composites Manufacturers > Source: https://netray.co/resources/ai-quoting-for-composites-manufacturers > Publisher: Netray (netray.co), AI and integration engineering for ERP and manufacturing systems. > Section: Knowledge Base ## Short answer How AI helps composites manufacturers quote faster: reading RFQ drawings and ply books, matching similar past parts, and drafting an estimate an estimator approves. ## Category ai-automation ## Content **Intro:** AI quoting for composites manufacturers reads the RFQ package, extracts materials, ply counts, cure requirements and quality clauses, finds similar past parts with their actual hours and material yield, and drafts a cost build for the estimator to approve. It shortens the slow part of quoting, which is gathering facts, without replacing estimator judgment. For firms bidding aerospace, defense, marine, transportation or industrial composite parts, the benefit is faster turnaround and estimates anchored in what jobs actually cost. This page explains the workflow and its limits. **Sections:** #### What Is in a Composites RFQ **Body:** A composites RFQ is often a mix of drawings, a 3D model, a ply table or laminate specification, a material specification such as an approved prepreg system, a process specification for layup, cure and NDI, quality clauses, packaging rules and a quantity breakdown with long-term agreement options. The cost drivers are scattered across these documents: a note on drawing sheet three may require a ply sequence verification, a specification may demand a vacuum integrity check at set intervals, and an NDI note can add ultrasonic inspection time. Missing one of these in an estimate is how a profitable-looking job turns into a loss. **Bullets:** - Material system and approved sources - Ply count, orientation and local reinforcements - Cure recipe, pressure and post-cure requirements - NDI method and acceptance criteria - Special packaging, marking and documentation #### How the AI Workflow Runs **Body:** A quoting assistant ingests the package, extracts the requirements above with a citation to the page and line, and builds a structured summary. It then searches your own history in the ERP and quote library for similar parts by material system, size, ply count and process route, and returns the actual routing, hours by operation, material yield and final margin. From these it drafts a cost build, flagging every assumption where history is thin. The estimator reviews, edits and approves. Nothing is sent to the customer or written to the ERP without human approval, and every number links back to its source so the review is quick. #### Why Private Deployment Matters **Body:** Composites work for defense and aerospace programs often arrives with export-controlled drawings and controlled unclassified information. Uploading those to a public AI service can create a compliance problem for the customer. A private deployment runs open-weight models on the shop's own GPUs, or in its controlled cloud environment, with access controls matching the drawing vault. It also keeps pricing history, your most commercially sensitive data, on your own systems. The architecture lets the customer apply their own ITAR and CMMC obligations; it does not replace their compliance program. #### What Still Needs a Human Estimator **Body:** AI is good at reading and retrieval, and weaker at judgment. It should not decide how to price a program with real development risk, whether a tight tolerance on a bonded assembly is achievable, whether to absorb tooling to win a long-term agreement, or how a scheduling squeeze affects the promised lead time. It also cannot know about a new cure oven that cut your cycle time last month unless that data is in the history. Treat the draft as a fast, well-sourced starting point, and keep a feedback loop where estimators correct errors so the retrieval gets better. #### When This Is Not Worth It **Body:** If you quote fewer than perhaps ten composite jobs a month, or most work is repeat parts with stable prices, the effort to set up retrieval over history may not pay off. A well-kept template spreadsheet and a disciplined actuals review will perform nearly as well. The value rises with RFQ volume, document complexity and the number of estimators, and when estimating knowledge sits in one person's head. A reasonable test is to check how many hours go into reading packages and finding comparable jobs; if that is the bulk of the work, the case is strong. **Cta:** Send a sample composites RFQ and Netray will show a draft extraction and similar-job lookup running on your own infrastructure, with sources visible for each figure. **Faq:** #### Can AI read composite drawings and ply tables? **Answer:** It can extract text, notes and tables from drawings and specifications, and read structured ply tables reliably. Geometry from raw drawings is less reliable, so estimators should confirm key dimensions. The best results come from combining extraction with a human check on anything that drives cost, such as ply counts or NDI notes. #### Is it safe to use AI on ITAR composite drawings? **Answer:** Not with public cloud AI tools. A private deployment on your own hardware and controlled network can keep drawings inside the boundary you already maintain, with access control and logging. Your Technology Control Plan and compliance team still decide what is permitted, so involve them before any rollout. #### How much faster is AI-assisted composite quoting? **Answer:** Savings come from the reading and comparable-search steps, which often take most of an estimator's time on complex packages. Many shops could see that portion shrink from hours to minutes, but results depend on history quality. Pilot on past RFQs with known outcomes before estimating a number for your shop. ## Related Slugs - ai-quoting-aerospace-defense-manufacturers - itar-compliant-ai-tools-manufacturing - cmmc-compliant-ai-deployment - ai-document-processing-erp ## Search terms AI quoting composites, AI RFQ review composite parts, automated estimating composites manufacturer, AI for ply book extraction, composites quoting software, AI estimating carbon fiber parts --- Talk to an engineer: https://netray.co/contact?intent=erp_ai | Machine catalog: https://netray.co/agent/catalog.json