AI translation is changing how language services are delivered. Machine translation output is improving fast, and demand for MTPE is growing across industries. But as production methods evolve, one question matters more than ever for buyers of translation services: how is quality actually managed when AI is part of the process?

This March, Hansem Global completed its ISO 17100 and ISO 18587 certification audit with Austrian Standards, passing with no corrective actions or findings. The four-hour audit examined the company’s end-to-end translation operations — from project intake to final delivery — with particular attention to how AI-assisted workflows are governed within a structured quality framework.

Here is what the audit examined and what it revealed about how Hansem Global operates.

A Project Management System Built Around Accountability

Hansem Global does not treat translation as a single production step. Every client project moves through a defined workflow: Pre-production, Production, and Post-production, each with clear responsibilities and checkpoints.

During the audit, project managers demonstrated how this works in practice. Before production begins, the team analyzes client requirements, prepares reference materials, defines the work strategy, and selects qualified resources. During production, progress is tracked and communication with linguists is managed actively. After delivery, client feedback is documented and reflected in future assignments.

This is not a theoretical framework. The audit verified that these steps are consistently followed across real client projects. For buyers, this means that a project entering Hansem Global’s pipeline is managed with the same discipline whether it involves 5,000 words or 500,000.

How MTPE Quality Is Controlled

With MTPE becoming a primary production method, the audit placed significant focus on how Hansem Global manages post-editing quality. The distinction matters: MTPE is not simply a linguist correcting machine output. It requires professionals who can evaluate fitness for purpose, contextual accuracy, terminology consistency, and alignment with client-specific requirements — all at once.

Hansem Global maintains a structured evaluation system for post-editors, tracking performance history and quality data across projects. Resource assignment is based on language capability, domain expertise, and demonstrated results, not availability alone. The audit confirmed that this system operates consistently across language pairs and project types.

These quality controls are supported by purpose-built infrastructure. Hansem Global’s AI Workstation, developed in-house, is the platform through which all AI-assisted translation is executed. It is not a generic MT plugin. The platform allows project teams to select the most suitable AI engine per project, process XLIFF files with integrated TM and term base connectivity, and generate project-specific glossaries within the same environment. By centralizing AI translation operations in a single controlled platform, Hansem Global ensures that terminology consistency, reference material alignment, and output quality are managed systematically — not left to individual linguist setups.

Resource Management at Scale

Large-scale, multilingual projects depend on the ability to match the right linguist to the right task reliably. Hansem Global’s resource operations cover the full cycle — from recruiting and vetting translators and reviewers, to skill-based assignment, performance tracking, and quality feedback.

The audit reviewed how resources are selected and evaluated by language and domain, and how quality consistency is maintained when projects span multiple languages and specialized subject areas. This operational layer is often invisible to clients, but it directly determines whether quality holds up at volume.

This resource operation runs on Hansem Global’s proprietary Resource Management System (RMS), an online platform that integrates the full resource lifecycle — from initial application and vetting through skill-based assignment, availability tracking, and performance evaluation. The system supports multi-dimensional filtering by language pair, domain expertise, and quality history, enabling project managers to match the right linguist to the right task with speed and precision. For large-scale multilingual programs, this eliminates the operational bottleneck that typically occurs when resource selection depends on manual coordination.

Security and Confidentiality

Translation projects routinely involve sensitive content — product launches, legal documents, financial disclosures, proprietary technical information. The audit examined Hansem Global’s internal security protocols and data handling practices, confirming that client assets are managed under documented security policies throughout the project lifecycle.

What the Audit Signals About the Industry

One of the more notable aspects of this audit was how the assessment criteria themselves are evolving. As MTPE becomes standard practice, the boundary between traditional translation and machine-assisted workflows is blurring. The auditor noted that ISO 17100 and ISO 18587 are moving toward integration, reflecting the reality that most production environments now combine both approaches.

Hansem Global has operated under both certifications for years — ISO 17100 since 2014 and ISO 18587 since 2020. As the standards converge, Hansem Global’s existing operational structure is already aligned with where the industry is heading.

Quality Is an Operating System, Not a Label

Certifications confirm that a system exists. But what matters to clients is whether that system actually works under real project conditions — tight deadlines, complex language pairs, domain-specific terminology, evolving AI tools.

Hansem Global’s audit results confirm that the answer is yes. The company’s quality management is not a policy document. It is an operating system that runs across every project, every language, and every delivery, and it has been doing so for over a decade.

For organizations evaluating translation partners, this is what operational readiness looks like.