When Amerequip began working with CADDi, their challenge was not a lack of data. It was the opposite.

For over 100 years, Amerequip has been a leading designer and manufacturer supporting OEM customers such as John Deere, Caterpillar, and Oshkosh Corporation, to name a few, with medium to heavy duty complex equipment and hydraulics manufacturing, new product design and prototyping, and other component part creation. Across these many projects, Amerequip manages thousands of drawings, customer specifications, BOMs, company-generated data, and cross-referenced part numbers across multiple systems. Engineers, quality leaders, and supply chain teams were frequently moving between LX ERP, shared network drives, cross-reference tools, and product drawing servers just to answer what should have been simple questions:

●  What assemblies use this part?

●  Is this part number already used internally?

●  Do we already have a drawing for this?

The information existed. But accessing it required things only known by individuals with historical context, multiple systems, and too many clicks. As Tim Dorn, Vice President of Engineering at Amerequip, put it, “The breadth of our operations drives a high volume of data across the organization.” The real constraint wasn’t capability. It was how quickly the team could move through that data to make decisions.

{{quote-1}}

A Common Problem: One Part, Many Numbers

One recurring issue involved mismatched part numbers between customers and Amerequip’s internal system. When a customer referenced a part number that differed from Amerequip’s internal numbering convention, the traditional workflow required searching the ERP for a cross-reference, navigating to a drawing server, opening multiple prints, and confirming the match manually. It was a multi-step process that depended heavily on experience and familiarity with the systems.

After implementing CADDi Drawer, that workflow changed. As Bryon Nolan, Head of Quality at Amerequip, described:

{{quote-2}}

‍

Instead of navigating between ERP and shared drives, Bryon typed the customer’s part number directly into CADDi. Relevant drawings surfaced immediately, along with cross-referenced internal numbers embedded within the documents themselves. What previously required multiple systems and manual validation became a single search.

From Drawing Search to Assembly Visibility

The impact extends beyond individual part lookups. As part of the quality review process, Amerequip team focuses on understanding a component’s application within the product, which is especially important during nonconformance reviews and change assessments. Historically, this required running a “where-used” report in ERP, then separately navigating to drawing servers to validate assemblies and prints. It was accurate, but slow.

With CADDi, engineers and the Amerequip Quality group can search for a part and simultaneously see the assemblies that reference it, related drawings, and embedded specifications in one view. Bryon summarized it simply:

{{quote-3}}

‍

In practice, this reduces system hopping and accelerates root-cause analysis, customer responses, and internal decision-making.

Avoiding Duplicate Parts and Purchase Orders

Another powerful example emerged from reviewing a customer bill of materials that listed a component with only a generic description; no drawing reference or additional specification to reference. In the past, that often led to creating a new internal part number and issuing a new purchase order (possibly a new supplier) simply because it was difficult to determine whether the component already existed.

Using CADDi’s keyword search and flexible matching logic, Kyle Behrendt from the engineering team was able to identify that the component was already used in another product under a different internal description. Instead of duplicating the part, they reused what already existed. What began as a search workflow evolved into a cost-control and part-standardization opportunity.

Kyle describes the ability to find these existing parts:

“A large portion of our inventory never came through engineering. Now, with keyword searches in CADDi Drawer, we can finally see those parts. It’s opened up access to components we didn’t even realize we had.”

Importantly, this was not driven by theoretical AI capabilities. It was enabled by structured, searchable engineering data brought into one environment. The team could finally connect information that had always existed but lived in separate silos.

Changing Behavior, Not Just Tools

The behavioral shift is becoming increasingly visible across the engineering and quality teams.. After several weeks of usage, Bryon shared:

{{quote-4}}

‍

 That change in sentiment reflects more than convenience — it reflects trust. CADDi is quickly becoming the first place people look, not an optional add‑on to an already complex workflow.

As Stella Rezabek explained, “To change behavior, you first have to understand where the real pain points are, and time has always been the biggest one.” The workflow interruptions weren’t the issue; the challenge was the amount of time required to gather information each time a challenge came up.

With CADDi Drawer’s ability to search part‑number data, extracted drawing text, and metadata using many combinations of filters, engineers can narrow their search far faster than before. Instead of manually checking multiple locations or running separate searches across systems, they can refine results in seconds based on the criteria they choose. Stella Rezabek described the difference directly:

“When you can filter by part numbers, keywords, and drawing text all at once, what used to feel like something that took ages becomes almost instant, and that speed lifts a weight you don’t realize you’ve been carrying.”

That reduction in time is influencing how teams respond to questions, review information, and make decisions. The ability to quickly confirm details is encouraging earlier validation and reducing hesitation during daily engineering and quality work.

For Tim, that adoption curve has been notable. “It’s not one of those tools where you start to learn it and it takes weeks to see the value. It’s coming on quickly. People are using it for ‘real world’ applications right away.”

A Shift in How Amerequip Sees Software Partners

As the engagement progressed, Amerequip’s view of the partnership began to shift. This was not a traditional software rollout where a tool is installed and left for the team to figure out. Instead, the implementation evolved through weekly working sessions, real-world use case discovery, and continuous iteration based on how engineers and quality leaders actually work. The focus was practical value, not feature deployment.

From the project team’s perspective, one of the strongest differentiators has been the way CADDi handles follow‑through and prioritization. As Stella Rezabek explained, “Not every item can be done immediately, and CADDi is honest about that. What stands out is how thoughtfully they prioritize action items. Nothing disappears, nothing gets ignored, and every ‘Let’s do it later’ still has a clear path forward. That level of accountability is rare, and it shows.”

For Tim Dorn, who has led multiple enterprise software implementations, the difference was clear:

“In my experience, new software adoption and realizing a positive ROI is often challenging. What’s been different here is the level of interaction and project management during the onboarding process. Without the CADDi team’s support, Amerequip’s adoption would not have happened as quickly or with the same level of impact.”

What started as an effort to improve drawing search is becoming something more strategic: a unified engineering knowledge layer that connects drawings, assemblies, specifications, and cross-referenced part numbers into one accessible system. At its core, the transformation is about reducing friction in decision-making — replacing tribal knowledge and system hopping with a single, reliable source of truth.