AI Platform Slashes Search Time by 70% for Auto Supplier

CHICAGO, IL – May 19, 2026 – In an industry defined by razor-thin margins and relentless quality demands, Tier-1 automotive supplier Neaton Auto Products Manufacturing (NAPM) has demonstrated a significant leap in operational efficiency by leveraging artificial intelligence. The company announced it has reduced critical engineering search times by as much as 70% after implementing an AI data platform from technology firm CADDi, turning four decades of fragmented information into a unified intelligence hub.

The collaboration highlights a pivotal trend in manufacturing: the move beyond simple digitalization toward a more profound, AI-driven transformation. By consolidating over 140,000 documents from disparate systems—including complex CAD files, ERP data, and even handwritten notes—NAPM is providing a blueprint for how legacy manufacturers can unlock hidden value and empower their workforce in the era of Industry 4.0.

Taming Decades of Disparate Data

Like many established manufacturers, NAPM, a key supplier of steering wheels and airbag modules to major automotive OEMs, faced a common yet persistent challenge: its most valuable asset, engineering knowledge, was siloed. Critical design specifications, quality reports, and procurement histories were scattered across multiple shared drives, complex folder hierarchies, and legacy PLM systems. This data fragmentation, a widespread issue across the sector, created daily friction, slowing down everything from design validation to quality investigations.

"In manufacturing, we have already gone through digitalization," explained Naomi Noda, Vice President of Design Engineering at NAPM. "Now, companies are shifting toward AI implementation. To make AI effective, digital assets need to be unified. Development, production, quality and shipping—digital unification is about linking all of those departments into one central system so the data can be fully utilized."

To bridge this gap, NAPM partnered with CADDi to deploy its CADDi Drawer platform. The system ingested the company’s vast archive of 140,000 documents, using patented AI and Optical Character Recognition (OCR) to parse and structure the information. This process transformed static files, including scanned legacy drawings with handwritten annotations, into a dynamic, searchable database. Engineers can now use keyword searches to find specific dimensions or material types, or use the platform's powerful similarity search to instantly locate visually similar parts from decades-old designs, a feature previously impossible.

This move aligns with a broader industry push to create a "single source of truth." Research shows that manufacturers are increasingly turning to AI to connect fragmented data from production, supply chains, and management. By doing so, they can enable the real-time decision-making necessary to compete in a volatile global market. The success at NAPM saw platform adoption grow by 183%, expanding from an initial 30 users to 85 active accounts as its utility spread across departments.

From Hours to Minutes: Quantifying the Impact

The most immediate and dramatic impact of the data unification project has been a massive reduction in time spent on non-value-added tasks. NAPM engineers estimate they have cut drawing search time by 40% to 70%. Hours previously lost navigating convoluted folder structures are now redirected toward core responsibilities like design innovation, validation, and complex problem-solving.

This efficiency gain extends directly to the factory floor and quality control. Beth Crose, NAPM's Quality Control Manager, detailed the tangible benefits for her team. "For QA-related searches, we reduced the time from about 3 minutes and 17 seconds down to 1 minute and 30 seconds. That’s a savings of 1 minute and 47 seconds, or about 50% faster," she stated.

Crucially, the ease of access has changed how teams interact with data. "We are actually using drawings more now because they are easier to access," Crose added. "Previously, the effort required to find information limited how often people used it. Now that barrier is gone." This shift not only accelerates root cause analysis for quality issues but also fosters a more data-driven culture throughout the organization.

The project underscores a key benefit of AI in the workplace: empowering employees. By automating tedious administrative work, the platform allows skilled engineers and technicians to focus their expertise where it matters most, boosting both productivity and job satisfaction. This is particularly vital in a sector facing a shortage of skilled labor and the impending retirement of veteran employees with decades of tacit knowledge.

The Strategic Push into Procurement

Building on the success in engineering and quality, NAPM is now turning its attention to another critical area: procurement. The initial driver for partnering with CADDi, according to Noda, was to enhance purchasing capabilities and gain better control over costs.

"The main question with procurement is always how cheaply we can purchase components, since that directly affects profitability and what we can offer to customers," Noda remarked. Before the AI platform, NAPM’s procurement teams had limited ability to validate supplier quotes against historical pricing for similar parts, hindering their negotiating power.

With the centralized data in CADDi Drawer, the foundation is laid for the next phase using CADDi Quote. The goal is to create a dynamic cost table based on historical information. "We can look at similar past parts and generate a cost reference," Noda explained. "When we receive a quote, we can compare it and evaluate whether the pricing is appropriate. If a quote is higher, we can use that information to negotiate with suppliers."

This strategic approach transforms procurement from a reactive, administrative function into a proactive, data-driven one. By structuring historical part and cost information into reusable data tables, the system will enable procurement specialists to spend less time on manual data gathering and more time on strategic sourcing and supplier relationship management.

A Blueprint for Modern Manufacturing

NAPM's story is not an isolated one. CADDi has reported similar successes with other industrial giants, including Subaru, which saved hundreds of hours per month on drawing searches, and Sumitomo Drive Technologies, which cut search time by up to 90%. These cases collectively signal a maturing of Industry 4.0, where AI is not just a buzzword but a practical tool for solving long-standing operational bottlenecks.

While the market includes major players like Google Cloud and IBM, CADDi has carved out a distinct niche by acting as a unifying layer that complements, rather than replaces, a company's existing ERP and PLM systems. Its unique ability to process unstructured and legacy data makes it a powerful tool for established manufacturers with deep historical archives.

As the automotive industry continues to navigate intense cost pressures and technological disruption, the ability to rapidly access and leverage historical data has become a significant competitive advantage. By transforming its data archives from a liability into an asset, Neaton Auto Products Manufacturing is not just improving its own bottom line—it is demonstrating a clear and repeatable path for others to follow.