Nichirin Group has manufactured automotive components for more than 100 years. In factories, drones equipped with sensors handle inventory checks that previously took employees days to complete walking the floor. North America is leading much of this work, with successful approaches earmarked for rollout to facilities in Europe, Asia, India and Japan.
The company holds a clear view: It cannot remain stable without continuing to innovate and adapt. That stability depends on its people, and as the company adds new locations and functions across the U.S., it wants employees at every level to take ownership.
An Archive That Required an Expert to Navigate
In its Tennessee division, the company is investing in AI data tools to make 24 years of engineering history accessible to every employee on day one. The CADDi AI data platform deployment is one part of that larger investment, and the results are already shaping how Nichirin builds elsewhere.
Before CADDi, accessing drawings, BOMs and historical data required exact part numbers and a heavy reliance on the "tribal knowledge" of senior staff. This created significant information silos that slowed onboarding and daily operations for the entire team.
Preserving and Activating Global Veteran Knowledge
Although Nichirin has operated globally for more than a century, leadership recognized that sustaining growth required making local employees more self-sufficient by creating a knowledge-sharing infrastructure that could help drive innovation and long-term expansion.
Japanese expatriate and veteran staff embodied years of experience and contextual knowledge. Other employees routinely routed questions through them, and newer hires spent close to a year building enough familiarity with drawing structures and part-number logic before they could handle related tasks independently.
The most important documents, including engineering drawings and technical reports, were controlled by only a few people, with local staff often having to ask where specific files were located.
When CADDi Drawer was first proposed, there were concerns about the scale of effort required: Uploading over two decades of drawings, documenting historical conventions, linking engineering records to commercial data across systems that had never been connected. Instead, the value showed up before the work was even finished.
Building an Intelligence Hub for Company-wide Access and Enablement
Nichirin's engineering and commercial records were saved in separate systems with no shared structure connecting them. Drawing formats and part-numbering conventions had shifted multiple times, and sales teams searching for historical pricing had to move across spreadsheets, PDFs and archived folders, which meant producing estimates rather than verified figures if the right record couldn't be located in time.
The CADDi team began by interviewing Nichirin staff to map how part numbers had been structured across different periods of the company's history. CADDi Drawer extends standard optical character recognition with configurable logic that identifies which numbering rule applies to a given drawing based on its date, then extracts the correct part number from there.
The system was configured to apply the right numbering rules based on a drawing's date, extract the correct part number and link it to related BOM and commercial records through that shared key. A sales employee could then enter a customer name, material type or component description and retrieve drawings alongside verified pricing history in a single workflow.
After implementing CADDi, the team reduced reliance on individual knowledge to improve quoting speed and cross-functional decision making. This cultural shift resulted in notable behavior changes:
- Employees stopped routing basic location questions through higher-level employees, freeing them to focus on work that actually required their experience and judgment.
- Employees began going directly into CADDi Drawer instead of asking repeated questions.
- The quality of questions improved because employees were doing their own research first, saving time for veteran staff and building confidence for staff in training.
Bridging Technology Adoption Hurdles with Visible Impact
Experienced employees are often hesitant about digitization efforts because they can feel disruptive to long-established workflows. What gets them on board is positioning the transition as a way to preserve operational knowledge for the next generation of employees, especially as manufacturers face growing workforce and succession challenges.
Previously, drawing-related tasks required close to a year of accumulated context before a new hire could handle them independently. With CADDi Drawer in place, new employees accessed engineering and commercial records from the start and moved into substantive work months earlier than before.
For younger sales employees, access to historical project data changed what they could do independently. Before, estimating pricing or quantities meant either tracking down someone with historical context or working from guesswork. Now they search for past projects directly and build estimates from verified precedents, improving both the speed and accuracy of customer responses.
With aggressive team expansion, investment in AI and data tools signals what kind of environment new hires can expect to work in, which is increasingly important for younger workers evaluating long-term career growth in U.S. manufacturing.
AI-Driven and Built to Scale Workforce Empowerment
With the success of the Tennessee technology deployment, Nichirin is applying the strategy to expand the intelligence into more sites, expanding to Nichirin Flex USA, with facilities in El Paso, Texas, and Juarez, Mexico, so new sites start with a searchable, connected archive rather than waiting years for institutional context to develop.
Nichirin Tennessee is also transitioning responsibilities currently held by senior staff to local management. North America is serving as early proving ground, with the possibility of similar approaches being explored across its global group companies down the road.
Across U.S. manufacturers facing a tighter labor market, the same dynamic appears: Critical operational knowledge concentrated in a small number of long-tenured employees. The companies that succeed at localization are the ones that treat that knowledge as something to engineer into the operation, not something to recruit around.
