Many industrial organizations operate powerful machine learning applications localized to their immediate environment, but moving these tools into a global cloud infrastructure while maintaining functionality presents a major hurdle for the industry.

NEW YORK CITY, NY / ACCESS Newswire / June 30, 2026 / Quality management processes have long revolved around 2D PDF blueprints. These files hold critical dimensions and inspection specs that human operators usually interpret and key into digital systems. This manual work turns the engineering "source of truth" into a potential source of data entry errors.

In sectors like medical manufacturing and aerospace, a single incorrect tolerance can lead to serious results. The challenge arises because 2D drawings are unstructured image data. Few software creators have successfully automated the extraction of meaningful data from these images at scale.

High QA solved this via an AI-powered OCR engine that translates PDF blueprints into structured data, maintaining design accuracy. Yet, bringing this resource-heavy engine to a global cloud environment created specific technical difficulties.

A CHALLENGE BEYOND TYPICAL MIGRATIONS

While standard cloud migrations involve basic containerization and data movement, such tactics fail for machine learning stacks designed for on-premises gear. Moving these systems can lead to latency and performance drops when separated from local shop floor hardware.

For High QA, serving worldwide networks in automotive, energy, and defense required overcoming regional constraints. The system needed a global architecture meeting rigorous standards like FedRamp, CMMC 2.0, and SOC 2 across various regions.

Global scale was mandatory for High QA. Serving sectors like aerospace, medical devices, energy, heavy machinery, and defense-where supply chains cross borders-requires a

quality platform that functions globally, not just in one region. The goal was to provide consistent service for users in Asia, Europe, and the Americas, adhering to frameworks like CMMC 2.0, FedRamp, and SOC 2.

"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," said Ephy Torenberg, Chief Operating Officer at High QA. "To support worldwide users with consistent performance, we needed to re-architect this complex, resource-intensive solution for the cloud."

Moving from simple migration to a fundamental re-architecture is a necessary step for modernization in manufacturing technology. High QA's journey serves as a guide for this demanding transition.

THE INTERNAL CHALLENGE

A significant challenge was organizational: the internal staff was initially wary of collaborating with outside teams. This is a common reaction when specialized engineers manage proprietary AI; earning trust requires demonstrating genuine expertise.

This sentiment is frequent in the manufacturing tech sector. Engineers who have spent years developing proprietary AI possess a hard-won, detailed knowledge of the system that external partners cannot easily replicate. Skepticism about whether an outside firm can truly add value-rather than slowing things down or creating work-is an obstacle that must be overcome.

High QA partnered with Commit, an AWS Premier Partner, utilizing an "expanded team" approach. Commit engineers worked directly alongside High QA's internal staff to co-create architectural solutions.

The primary migration concluded in two months, with the partnership successfully demonstrating its value to the internal engineering team within that same timeframe.

"By expanding our team across geographies, boundaries, and languages, High QA and Commit have become one unified team working toward a shared mission," Torenberg said.

"When we look for a partner, we look for one who truly understands architecture, operates with transparency and professionalism, and is fully committed to our success."

MIGRATION REQUIREMENTS

The technical approach focused on three pillars: configuring AWS resources for high-speed AI operations, creating a multi-account landing zone to meet specific commercial and defense compliance needs, and ensuring seamless knowledge transfer so the internal team could manage the system independently.

THE LARGER CONTEXT

High QA's experience confirms that effective digital transformation in manufacturing relies on re-architecting rather than simple migration. It also highlights how professional trust and a shared vision are essential components of technological success.

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

Company Details

Company Name: COMMIT
Contact Person: Media Relation
Email: info@commit.us
Phone: 16672060208
Website: https://commit.us

SOURCE: COMMIT