What if data could turn vehicle inspections into insight?

‍Standardizing inspections with Domo + AWS

Because every jurisdiction has its own unique rules for vehicle safety and emissions, Opus has built a platform that combines best-in-class vehicle diagnostic and inspection technology with the ability for customization to meet local requirements. However, this approach meant Opus struggled with a fragmented data environment that made it nearly impossible to view performance holistically or identify best practices that could be shared across programs.  

“When I joined Opus about three years ago, the first thing I noticed was that we didn’t have a single platform for business intelligence across all the jurisdictions we manage. Everyone likes to do things their own way, but that creates challenges when you’re trying to create systems to support so many different jurisdictions,” Harlow said.

In addition, much of Opus’s infrastructure was still tied up in disconnected legacy systems collected over many years as part of a series of acquisitions. As a result, each state ran its own instance of a legacy relational database management system, with data configured in different ways. Maintaining separate databases was costly to maintain and difficult to scale, requiring a heavy manual effort to update or change.  

While Opus originally added Domo to act as its data lake and single source of reporting, it soon identified an opportunity to leverage Domo and AWS together to modernize its underlying infrastructure. Working with Domo and AWS, Opus began migrating its legacy relational database management system on a state-by-state basis to AWS systems.  

Opus now stores the majority of its relational data in AWS RDS (including Aurora) and SQL on EC2, for cost-optimized data storage, positioning the company to eventually sunset its legacy relational database management systems.  

To make the integration seamless, Opus relies on the AWS API Gateway to connect Domo with its back-end systems. This allows Opus to do things like periodically push vehicle inspection data on its platform to state systems to update registration records. API Gateway and AWS Lambda handle that process securely and efficiently, with Domo serving as the front end for initiating and managing the exchange.  

“We not only use Domo to ingest data and see it, but also to write data out. Today we have a hybrid system where Domo powers our reports and dashboards while also serving as the front end for putting our data into AWS,” Harlow said.

Preparing for AI workflows

With Domo and AWS working together, Opus has transformed how it manages inspection data nationwide. Opus used Domo to create a white-labeled portal called Opus Insights that customers can log into for easy access to administrative tools, standardized data, and ad hoc reporting so government agencies and repair centers can track performance and uncover trends.  

“We’ve embedded Domo directly into our platform so users can track anomalies and perform audits from the same interface. Having a single interface makes everything seamless. Our users don’t even realize they're in two different systems,” Harlow said.  

By using Domo and AWS to consolidate reporting and modernize its infrastructure, Opus has dramatically reduced the time and effort it takes to support its customers. Instead of maintaining separate systems for each customer, Opus can maintain a single platform, allowing it to make changes and upgrades faster and more efficiently.  

“We expect to shrink our software maintenance efforts by as much as 50 percent and speeding up customer deliveries with Domo and AWS,” said Harlow.

With its data now centralized on AWS and actionable through Domo, Opus is prepared for its next phase of innovation. The company is experimenting with Agent Catalyst, Domo’s intelligent agentic AI platform designed to create autonomous agents that independently manage entire business processes.  

One workflow Opus is building is an agent that can automatically transform 600-page customer-specific requirements into structured documentation for the engineering team, saving time while improving consistency and scale.  

“We won’t have to find a separate platform for AI workflows, because we can do it all within Domo,” Harlow said. “Improving the way we do requirements could be a game changer, and that’s just the start of the technology’s potential.”

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