AI for manufacturing: win more deals, price them right

AI extracts part specifications from customer documents (RFQs, drawings, CDLs), cross-references your ERP history and past quotes, and assembles accurate quotes in minutes instead of 15-30 minutes. We use a hybrid approach: deterministic scripts handle structured, repeatable fields while AI reasoning handles the variable content that requires judgment. Your subject matter experts focus on pricing strategy and relationship building instead of data assembly.

No. AI augments your team by handling repetitive document assembly and data extraction, freeing your experts to focus on relationship building, complex engineering decisions, and strategic pricing. Our approach pairs AI with your subject matter experts, not replacing them. In fact, AI makes their expertise more valuable by ensuring it gets applied consistently across every quote.

Most manufacturing clients see measurable improvements within the first 2-4 weeks. Our 8-week sprint model delivers a validated, production-ready workflow. Jet Parts Engineering achieved a 50% reduction in BERP document creation time and 3x parallel processing throughput within their sprint cycle. Precision fabricators and custom parts manufacturers typically see similar timelines.

Most manufacturers use cost-plus pricing: raw materials + standard markup. But some jobs are worth more based on urgency, customer relationship, complexity, or competitive landscape. Value-based pricing uses signals from your order history, customer conversations, and market data to price based on the value you deliver, not just your costs. AI makes this practical by surfacing these signals automatically instead of relying on gut feel.

Absolutely. Our engagements are designed specifically for small-to-mid-size manufacturers, not enterprise giants with unlimited IT budgets. We've worked with companies processing 25-100 orders per month who see outsized returns because AI eliminates bottlenecks that disproportionately affect smaller teams. PE-backed manufacturers in particular find this compelling because it drives EBITDA improvement through efficiency gains without adding headcount, with clear payback periods.

No. We build AI workflows that connect to your existing systems like Epicor, JobBOSS, SYSPRO, QuickBooks, Access databases, Excel, SharePoint, and email through secure connectors. There's no rip-and-replace. The AI layer works on top of your current infrastructure, pulling data from wherever it lives today.

All data stays within your infrastructure or approved cloud environments with enterprise-grade security. We don't train models on your data. Our approach uses AI as an orchestration layer that processes your documents on-demand without storing proprietary information. For aerospace and defense clients, we work within ITAR, DFARS, and CMMC compliance requirements and can scope engagements to operate entirely within approved environments.

High-mix, low-volume is actually where AI delivers the most value. When every order is different, your team can't rely on templates or standard pricing, so they reason through each quote individually. AI captures the reasoning patterns from your experienced team and applies them consistently, even across thousands of custom part configurations. One manufacturer we talked to had 10,000 custom parts and engineers starting from scratch each time. That's exactly the scenario where AI search and knowledge capture transforms productivity.

We offer tiered options so you can start small and scale up. A Tier 0 proof-of-concept starts at $4,500 over 4 weeks: we validate AI against your historical quotes and prove accuracy before you commit further. Most manufacturers choose a Tier 1 engagement ($15,000-$25,000 over 4-6 weeks), which delivers a working AI workflow for your highest-value bottleneck, like quoting or customer intelligence. Tier 2 builds core infrastructure like pricing engines or knowledge systems ($30,000-$45,000 over 8 weeks). Every engagement is outcome-based: half upfront, half upon verified success against metrics we agree on together. We scope it during the strategy call so you know exactly what you're getting before you commit.

We need one subject matter expert available for about 4-6 hours per week during the engagement, mostly in the first two weeks for knowledge transfer and workflow mapping. After that, involvement drops to a couple of hours per week for testing and feedback. We work around your team's schedule and production demands. The goal is to capture expertise efficiently, not pull your best people off the floor.

You own everything we build: the workflows, the code, the know-how. Our sprints include a structured handoff where we train your team to operate and improve the system independently. If you need ongoing hosting or support, we offer lightweight service agreements. The goal is to teach you to fish, not create dependency.