AI-Powered Quoting for Aerospace and Defense Manufacturers
AI-powered quoting for aerospace and defense manufacturers uses AI agents to read RFQ packages, extract technical and contractual requirements, match them against historical costs and current capacity, and assemble a draft quote for estimator review, cutting turnaround from 1-3 weeks to 1-3 days. In A&D, the quote is not just a price: it is a compliance document spanning ITAR handling, DFARS flow-downs, AS9100D quality clauses, and traceability commitments. Shops that quote faster win disproportionately, because primes increasingly award to the first compliant, credible bid. This guide explains how the AI quoting workflow works and what it returns.
Why A&D Quoting Takes Weeks Today
A typical defense RFQ package arrives as 50-300 pages: drawings with flag notes, specifications, a statement of work, quality clauses (Q-notes), and a terms document carrying dozens of FAR/DFARS flow-downs. An estimator must extract material callouts and special processes (heat treat per AMS 2750, NDT per NAS 410-certified personnel, plating, passivation), identify which operations are outsourced, check clause acceptability, find comparable historical jobs, and build labor and material cost. Each step is manual reading against tribal knowledge. At most mid-tier shops this consumes 8-40 estimator hours per quote, quotes queue for days before anyone starts, and 30-60 percent of that effort is spent on bids that never convert.
What the AI Agent Actually Does With an RFQ Package
A quoting agent processes the package the way a senior estimator would, but in minutes. It parses drawings and specs to extract requirements, classifies the part against your historical work using geometry notes and material, and pulls actuals from your ERP.
- Extract material specs, tolerances, special processes, and flag notes from drawings and attach source citations
- Match the part to similar historical jobs in SyteLine or LN and surface actual routings, times, and margins
- Screen FAR/DFARS flow-downs against your accepted-clause library and flag exceptions (for example DFARS 252.225-7009 specialty metals)
- Assemble a draft cost buildup, material, labor by work center, outside processing, with every number traceable to a source
Keeping ITAR and CUI Inside the Quote Process
Most RFQ packages from defense primes contain export-controlled drawings, which is exactly why generic cloud quoting tools are a non-starter: uploading an ITAR drawing to an uncontrolled SaaS is a potential unauthorized export under ITAR 120.17. The compliant pattern runs the entire pipeline, document parsing, retrieval, and LLM inference, on-prem, inside the same boundary that already holds your controlled drawings.
- Process ITAR drawings only on inference hardware inside your facility with US-persons-only administration
- Enforce document-level permissions so estimators see only programs they are authorized for
- Log every extraction and draft to support your Technology Control Plan and CMMC audit requirements
- Never let quote data or drawings transit third-party AI APIs, even encrypted
The Business Case: Speed, Accuracy, and Win Rate
The math is direct. If estimators spend 20 hours per quote and the agent cuts that to 6, a shop producing 40 quotes a month recovers roughly 560 estimator hours monthly, enough to bid more work without hiring. Speed compounds the effect: responding in 3 days instead of 15 puts you in front of primes while competitors are still in queue, and shops report win-rate improvements of 3-8 percentage points from responsiveness alone. Accuracy improves too, because drafts are grounded in historical actuals rather than optimistic estimates, narrowing quote-to-actual variance and protecting margin. Against a typical $60,000-$120,000 on-prem deployment, most A&D shops model payback in 6-12 months before counting any win-rate gain.
How Netray's Quoting Agents Work With Your ERP
Netray deploys on-prem AI quoting agents purpose-built for aerospace and defense manufacturers on Infor SyteLine, CloudSuite Industrial, LN, and Baan. The agent ingests RFQ packages, extracts requirements with citations, matches historical jobs through direct ERP integration (IDOs on SyteLine, standard APIs on LN), screens flow-down clauses against your playbook, and hands the estimator a reviewable draft quote, all without any data leaving your network. Customers report quote turnaround dropping from 10-15 days to under 3, estimator hours per quote cut by 60-70 percent, and cleaner clause exception logs at contract review. Deployment is a fixed 90-day engagement including your historical-quote index and ITAR-aligned access controls.
Frequently Asked Questions
How does AI quoting handle ITAR-controlled drawings?
By running the entire pipeline on-premises. Drawings are parsed, indexed, and processed by an LLM on GPU hardware inside your facility, within the same boundary that already stores controlled technical data, with US-persons-only administrative access and full audit logging. Nothing transits a third-party AI API. Cloud quoting tools that upload drawings to external services create potential unauthorized-export exposure under ITAR and are not suitable for defense RFQs.
How much time does AI save per manufacturing quote?
Shops typically report estimator time falling from 8-40 hours per defense quote to 2-8 hours, a 60-70 percent reduction, because the AI handles requirement extraction, historical job matching, clause screening, and first-pass cost buildup. Turnaround drops from 1-3 weeks to 1-3 days since quotes no longer queue for scarce estimator attention, and estimators focus on judgment: risk, margin strategy, and capacity.
Can AI check FAR and DFARS flow-down clauses in an RFQ?
Yes. An LLM compares the RFQ's terms against your accepted-clause library and flags deviations, new clauses, and known problem provisions such as DFARS 252.225-7009 specialty metals restrictions or intellectual property assertions, with citations to the source page. Contract review remains a human decision, but AI screening reliably catches clause changes buried in 100-page packages that manual review misses under deadline pressure.
Key Takeaways
- 1Why A&D Quoting Takes Weeks Today: A typical defense RFQ package arrives as 50-300 pages: drawings with flag notes, specifications, a statement of work, quality clauses (Q-notes), and a terms document carrying dozens of FAR/DFARS flow-downs. An estimator must extract material callouts and special processes (heat treat per AMS 2750, NDT per NAS 410-certified personnel, plating, passivation), identify which operations are outsourced, check clause acceptability, find comparable historical jobs, and build labor and material cost.
- 2What the AI Agent Actually Does With an RFQ Package: A quoting agent processes the package the way a senior estimator would, but in minutes. It parses drawings and specs to extract requirements, classifies the part against your historical work using geometry notes and material, and pulls actuals from your ERP..
- 3Keeping ITAR and CUI Inside the Quote Process: Most RFQ packages from defense primes contain export-controlled drawings, which is exactly why generic cloud quoting tools are a non-starter: uploading an ITAR drawing to an uncontrolled SaaS is a potential unauthorized export under ITAR 120.17. The compliant pattern runs the entire pipeline, document parsing, retrieval, and LLM inference, on-prem, inside the same boundary that already holds your controlled drawings..
Send Netray a sample RFQ package and see a grounded draft quote produced on-prem, with every number traceable to your own history.
Related Resources
ITAR-Compliant AI Tools for Manufacturing: Requirements and Options
ITAR-compliant AI tools for manufacturing: what export control rules mean for LLMs, which vendors qualify, and how to deploy AI without a deemed-export risk.
AI & AutomationAI in Aerospace MRO Operations: Use Cases and ROI
AI in aerospace MRO operations: predictive maintenance, automated part records, repair quoting, and tech-log analysis. Real use cases, ROI figures, timelines.
AI & AutomationOn-Prem AI for Defense Contractors: The Complete Guide
On-prem AI for defense contractors: deploy LLMs and AI agents inside your CMMC and ITAR boundary. Architecture, hardware costs, timelines, and vendor options.