A case study analyzes how Neaton Auto Products Manufacturing advances AI adoption by unifying four decades of data across engineering, procurement, and quality control.
CHICAGO—A new case study compiled by CADDi explores how the Tier-1 automotive supplier Neaton Auto Products Manufacturing (NAPM) applied the CADDi AI Data Platform to centralize critical design knowledge and enable faster engineering workflows and quality investigation.
CADDi, a global technology company, is developing an AI data platform for manufacturers. In the case study, CADDi analyzes cost control and efficiency gains for NAPM, the company said in a release.
Transforming 140,000 assets into unified manufacturing intelligence across departments
Manufacturing is heading into another significant era of transformation, according to NAPM Vice President of Design Engineering Naomi Noda.
“In manufacturing, we have already gone through digitalization. Now, companies are shifting toward AI implementation,” Noda said in the release. “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.
“Companies that are successful in this area have systems that link information together so AI can use that data,” Noda continued. “That allows them to identify errors in a timely manner and make faster decisions.”
CADDi is an AI powered data platform that makes design and supply chain data accessible and actionable for manufacturing teams. As usage of CADDi spread, adoption of the CADDi platform reportedly increased from an initial 30 users to 85 active accounts, the release stated.
Before partnering with CADDi, critical engineering knowledge was distributed across multiple shared drives and complex folder hierarchies. Locating the correct specifications, confirming the latest revisions, and coordinating across teams required manual navigation that slowed down daily operations. Neaton Auto Products Manufacturing loaded over 140,000 documents into a unified CADDi platform, consolidating information across PLM, ERP systems, and scanned documents, including handwritten notes that were previously difficult to search and reuse.
“This created a foundation for manufacturing intelligence across engineering, quality, and procurement,” the release stated. “Specifically, by consolidating drawings and related documents into a unified platform, NAPM engineers estimate they have reduced drawing search time by 40-70 percent. Hours previously spent navigating folders are now redirected to higher-value design and validation work.”
According to CADDi, quality control team members can now access drawings, design notes, and QA sheets from one place and move directly into root cause analysis without spending time gathering information across systems.
^P“For QA-related searches, we reduced the time from about 3 minutes and 17 seconds down to 1 minute and 30 seconds,” said NAPM Quality Control Manager Beth Crose, in the release. “That’s a savings of 1 minute and 47 seconds, or about 50 percent faster. This time reduction reflects closely what my team experiences as well. We are actually using drawings more now because they are easier to access. Previously, the effort required to find information limited how often people used it. Now that barrier is gone.”
Prioritized procurement efficiency and quoting workflow structure
Building on the successful deployment of CADDi Drawer, NAPM is reportedly exploring opportunities to further improve quoting efficiency and cost visibility using CADDi’s procurement platform, CADDi Quote. By connecting engineering drawings with quoting and procurement information, NAPM aims to support more efficient and consistent quotation workflows in the next phase of its digital transformation, according to the release.
^P“The main reason we chose to partner with CADDi was to improve procurement capability—that was the original objective,” Noda emphasized. “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. That is an ongoing challenge for the procurement department.”
The NAPM procurement teams were limited in their ability to validate supplier quotes against historical parts and pricing, which affected how effectively they could evaluate cost and negotiate with suppliers. This limited the time available for higher-value activities, such as evaluating quotations and making strategic sourcing decisions, the release said.
“With CADDi, we can pull together a lot of information from one place,” Noda continued. “For procurement data specifically, we are trying to create a cost table based on information in Drawer. We can look at similar past parts and generate a cost reference. 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 and ask why it is more expensive.”
By introducing CADDi Quote, NAPM aims to minimize these manual efforts while structuring historical part and cost information into reusable, searchable data tables. This enables procurement teams to focus more on quotation analysis and supplier strategy rather than administrative work.
Looking ahead, NAPM plans to expand the scope of suppliers and parts data in CADDi, with the goal of reducing procurement workload and enabling more strategic sourcing activities.
Headquartered in Tokyo and Chicago, CADDi was founded in 2017 by industry veterans Yushiro Kato and Aki Kobashi, formerly of McKinsey and Apple. Its flagship product, CADDi Drawer, uses advanced AI to centralize and analyze unstructured design and production data, helping manufacturers improve efficiency, reduce redundancies, and unlock innovation.