New York, NY – High QA faced a daunting challenge: migrating its precision AI engine to AWS without sacrificing the performance and speed that defined it. The transition demanded more than just a technical overhaul; it required a fundamental realignment of how two separate engineering organizations could operate as a single, cohesive team.
At its core, the issue was one of translation. High QA had dedicated years to perfecting an AI engine capable of a complex feat: taking static, 2D PDF drawings—a format virtually unchanged for decades—and transforming them into structured digital data. This process eliminated manual entry and interpretation risks, ensuring that design intent transitioned smoothly into the quality management lifecycle.
While the engine was effective, the real test was scaling it for a global user base. The platform was built specifically for the shop floor, with a machine learning and OCR stack optimized for local, on-premises processing power. While this architecture was fast, controllable, and tightly integrated into physical manufacturing environments, it was inherently local. This created a limitation for customers ranging from aerospace facilities in Texas to automotive suppliers in Germany and defense contractors in the UK.
The Migration That Could Not Fail
Cloud migration is a familiar concept in enterprise technology, but the difficulty varies wildly. While moving databases or web apps to AWS is standard, migrating a resource-intensive machine learning stack—particularly one coupled to shop floor hardware in regulated industries—is a unique challenge.
For High QA, the stakes were significant. Their platform serves essential industries such as aerospace, defense, energy, and medical devices, where quality management is a core operational requirement tied to safety and regulation. Any migration that introduced latency or compliance gaps would not be a mere inconvenience; it would create genuine business disruption for their customers.
“At the heart of the business is an advanced machine learning and OCR/AI engine that converts 2D PDF images into structured digital data,” said Ephraim Torenberg, Chief Operating Officer at High QA. “The platform was originally designed to run exclusively on in-house desktop systems optimizing computation resources locally and was tightly coupled to shop floor manufacturing environments.”
Re-architecting for the cloud meant balancing consistent global performance with strict security standards, such as SOC 2 and CMMC 2.0.The Partner Problem
Technology companies with specialized, proprietary AI often face a common organizational hurdle: the engineers who built the system are the most skeptical of outside help. High QA prioritized in-house capacity, deciding to bring in an external partner a major strategic shift.
They ultimately selected Commit, a global firm with deep expertise in manufacturing and AWS cloud architecture. Earning the trust of High QA’s internal engineering team was the critical first step.
“The engineering team had a strong preference for learning and building capacity in-house,” Torenberg said. “Overcoming this required a partner that could demonstrate technical credibility quickly, align closely with internal stakeholders, and establish a collaborative working model to support long-term success.”
Commit employed an “expanded team” model, embedding their engineers directly into High QA’s organization. Instead of working as a separate vendor, they focused on shared ownership of architectural decisions and transparent communication across time zones, building the long-term internal capability for High QA to operate the environment independently.Sixty Days to Credibility
The core migration was finalized in sixty days. This deliberate timeline served to prove value rapidly. A dedicated cloud architect led the effort, mapping out the AWS landing zone, security guardrails, and network segmentation. The architecture ensured that the machine learning stack maintained its local-performance standards while running in a distributed cloud environment. Both the performance and compliance requirements—including CMMC 2.0 and SOC 2—were met within that window.
The result is a quality platform with global reach that maintains the high performance expected from a locally-deployed solution.
What It Means for Manufacturing
High QA’s experience is a case study for the broader manufacturing sector as it shifts toward Industry 4.0. The lesson is that organizational hurdles—securing buy-in from proprietary-knowledge engineering teams—are often more complex than the technical ones. Success depends on shared ownership between both sides of the partnership.
“When we look for a partner, we look for one who truly understands the architecture, operates with transparency and professionalism, offers fair pricing, and is fully committed to our success,” Torenberg said. “With Commit, we found all of these qualities. By expanding our team across geographies, boundaries, and languages, High QA and Commit have become one unified team working toward a shared mission.”
For High QA’s customers, the result is clear: a quality management platform that operates at scale while upholding the stringent compliance standards their industries demand. The factory floor and the cloud are no longer separate domains.
ABOUT COMMIT
Commit is a global technology services firm founded in 2005 with offices in the United States, Israel, Canada, the United Kingdom, and Europe. An AWS Premier Solutions Integration Partner, Commit specializes in cloud architecture, AI-powered solutions, cybersecurity, IoT, and data analytics, with more than 1,200 projects completed for organizations across industries. commit.us
ABOUT HIGH QA
High QA provides integrated manufacturing Quality Management and Supplier Quality solutions built on the High QA 360 platform, helping manufacturers digitize and automate the full quality lifecycle across aerospace, automotive, medical, defense, energy, and heavy machinery sectors. highqa.com
