For global enterprises, quality assurance is rarely just about checking a box. It is about protecting brand reputation, ensuring user safety, and driving revenue across borders. While ISO certification serves as a critical baseline for the translation industry, the complexity of modern content demands more than a static stamp of approval.
True quality in the AI era requires a dynamic framework. It demands systems that can scale without breaking, workflows that enforce consistency automatically, and metrics that measure the actual outcome rather than just the process. By combining ISO rigor with advanced technologies like TranslationOS and Lara, organizations can move from simple compliance to a state of continuous, data-driven improvement.
Understanding the benchmarks: ISO 17100 and ISO 9001
To evaluate a translation service, it is essential to understand the specific standards that govern the industry. These standards provide a framework for consistency, but they serve different purposes within the supply chain.
ISO 17100: the translation service standard
ISO 17100 is the specific standard for translation services. It does not measure the quality of the translation itself (which is subjective) but rather the rigor of the process used to create it. It establishes requirements for:
- Resources: Ensuring linguists have the appropriate qualifications and experience.
- Pre-production: clearly defining project specifications and analyzing source content.
- Production: Mandating a specific workflow, typically involving translation followed by a separate revision by a second linguist.
- Post-production: Handling client feedback and closing projects.
ISO 9001: The quality management standard
ISO 9001 is broader. It applies to organizations across all industries and focuses on quality management systems (QMS). For a translation provider, ISO 9001 certification demonstrates that the company has documented processes for every aspect of its business, from customer service to IT security, and that it has mechanisms in place for continuous improvement.
While these standards are vital for establishing a baseline of trust, they were designed for a world of manual workflows. In an era where enterprises need to translate millions of words at speed, adhering to the letter of the law is not enough. You need technology that enforces the spirit of these laws at scale.
Beyond the certificate: A data-driven framework
Obtaining certification is a milestone, but maintaining quality at enterprise scale is an operational challenge. A certificate hangs on a wall; a quality framework lives in the daily operations of the business.
The limitation of traditional ISO compliance is that it often relies on manual checks. A project manager manually selects a translator based on a CV. A file is manually emailed to a reviewer. These human touchpoints introduce friction and the potential for error.
Translated approaches this challenge by embedding ISO principles directly into the code of our platforms. By automating the selection, workflow, and verification steps, we ensure that compliance is not an afterthought but a default state. This approach shifts the focus from “did we follow the process?” to “is the outcome excellent?”
Assembling the right team with T-Rank
One of the strict requirements of ISO 17100 is the professional competence of linguists. Traditionally, agencies meet this by collecting resumes and verifying degrees. However, a degree earned ten years ago does not guarantee proficiency in a specific niche domain today.
Technology allows for a more granular verification of competence. Translated utilizes T-Rank™, an AI-powered selection system, to fulfill and exceed this requirement. T-Rank goes beyond static qualifications. It analyzes the actual performance of translators across thousands of previous jobs.
The system evaluates linguists based on:
- Domain expertise: Has the translator successfully handled technical documentation or creative marketing copy?
- Real-time performance: What are their recent quality scores and responsiveness?
- Semantic matching: How closely does their past work align with the specific content of the new project?
By using data rather than just credentials, T-Rank ensures that the linguist selected is not just “qualified” on paper but is the absolute best match for the specific task at hand. This transforms the “resource” requirement of ISO 17100 from a static check into a dynamic performance optimization.
Enforcing a compliant workflow with human-AI symbiosis
ISO 17100 mandates a “four-eyes” principle: a translation step followed by a revision step by a separate person. This ensures that errors are caught and style is consistent.
In the past, raw machine translation (MT) was often seen as incompatible with high-quality standards. However, the industry has evolved. We do not use raw MT followed by post-editing in the traditional sense. Instead, we employ a model of Human-AI Symbiosis.
The role of Lara
Lara, our proprietary LLM-based translation model, supports the professional translator during the initial translation phase. Unlike generic models, Lara is trained to understand full-document context and adapt to specific terminology.
The translator works with Lara to produce the initial draft. This is not a passive “cleanup” of machine output. The professional linguist is in control, using the AI to speed up cognitive processing and ensure terminology consistency. This human-authored, AI-supported translation is then passed to a second human reviser.
Trust and traceability through TranslationOS
ISO 9001 emphasizes the importance of traceability and documented processes. In a high-volume localization program, maintaining a paper trail for every string of text can be impossible without a centralized system.
TranslationOS serves as the central nervous system for this data. It provides a complete audit trail for every project.
- Workflow enforcement: The platform prevents steps from being skipped. A project cannot move to delivery until the revision step is verified as complete.
- Data security: By centralizing assets in a secure cloud environment, TranslationOS protects client data more effectively than decentralized email exchanges.
This level of transparency enables stakeholders to verify compliance instantly. It turns the “documented process” requirement of ISO 9001 into a real-time dashboard of operational health.
Measuring success: From process to outcome
Ultimately, standards are about guaranteeing a result. While ISO focuses heavily on the process (how you get there), modern localization demands that we also measure the outcome (what you actually delivered).
Translated uses advanced metrics to quantify quality in ways that go beyond simple “pass/fail” compliance.
Time to Edit (TTE)
We measure Time to Edit (TTE), which tracks the time it takes a professional translator to refine the AI’s output. This is a crucial indicator of efficiency and utility. If the TTE is low, it means the AI provided high-value suggestions, allowing the human to focus on nuance. TTE has become an emerging standard for measuring the effectiveness of the translation pipeline.
Errors Per Thousand (EPT)
For quality assurance, we utilize Errors Per Thousand (EPT). This metric provides a standardized way to benchmark accuracy across different languages and content types. By tracking EPT, we can identify trends, spot potential issues with source content, or highlight training needs for specific linguists.
Continuous improvement as a standard
The most powerful aspect of ISO 9001 is the requirement for continuous improvement. In a manual workflow, learning is slow. A mistake made in one project might be repeated in the next because feedback loops are disconnected.
In a technology-driven framework, improvement is systemic. When a reviser corrects a translation in our system, that data point is not lost. It feeds back into the ecosystem.
- Lara learns: The AI model adapts to the correction, ensuring the error is not repeated in future suggestions.
- T-Rank updates: The translator’s quality score is adjusted based on the reviser’s feedback, influencing future job assignments.
- Memories update: The translation memory is updated in real-time, ensuring consistency across the entire enterprise.
This creates a system that gets smarter with every word translated. It is the ultimate expression of the ISO mandate to “continuously improve.”
Conclusion
ISO standards define a necessary foundation, but they do not guarantee quality at enterprise scale. True assurance comes from a living framework where certified processes are reinforced by data, automation, and human expertise working together. By combining ISO rigor with technologies such as T-Rank, Lara, and TranslationOS, organizations can achieve measurable quality, traceability, and continuous improvement across every language. To move beyond baseline compliance and build a translation quality system designed for scale, get in touch with Translated.