Most software localization workflows do not fail because of translation capacity. They slow down because the way teams share and maintain the needed context doesn’t scale.
Strings move quickly through automated pipelines, but understanding how those strings behave inside the product still requires manual explanation, extra reviews, and developer involvement. That gap has become one of the biggest bottlenecks in software localization today.
For many teams, translation itself is no longer the primary constraint in software localization. With established workflows, terminology, and automation, content moves efficiently through the pipeline.
What does not scale as easily is access to context.
Translators and reviewers frequently work with strings separated from the interface they belong to. They see text in files or CAT tools, but not how it appears, behaves, or changes inside the product. As interfaces become more dynamic and releases more frequent, this gap becomes more pronounced.
The result is familiar:
Clarification questions that interrupt workflows
Review feedback that arrives late or lacks precision
UI issues discovered during testing rather than translation
Developers stepping in to provide explanations or screenshots
Context becomes the bottleneck that slows otherwise efficient localization workflows.
Removing this bottleneck requires treating context as a first-class part of localization, not as supporting material added later.
Rigi by XTM is a visual software localization platform that brings real UI context directly into translation and review. As part of the XTM ecosystem, it is designed to work alongside Transifex workflows, adding the visual layer without disrupting how teams already localize at scale.
Translators and reviewers work with interactive previews of the interface, seeing text exactly where it appears in the product and how it behaves across different states.
This changes how translation decisions are made. Layout, tone, and usage can be validated while work is in progress, not after the fact. Feedback becomes specific and actionable. Many issues are resolved before they surface downstream.
When context is consistently available, localization workflows become lighter and more predictable.
Product teams gain confidence that localized interfaces reflect the intended user experience before release. Localization managers see review cycles shorten and coordination overhead decrease. Translators and reviewers spend less time clarifying intent and more time producing accurate output.
Lastly, through CI/CD integration via a CLI and built-in i18n testing, Rigi helps ensure linguists work on the correct files and latest version of the product. This reduces errors caused by outdated sources and minimizes the need for engineering involvement during localization.
The constraint shifts away from context sharing and back to planning and prioritization, where teams expect it to be.
Context remains relevant beyond UI translation.
Documentation, help centers, onboarding flows, and training materials all depend on accurate representations of the product. When these assets are recreated manually for each language, overhead grows quickly.
Because Rigi captures the live UI, the same context used during localization can support scalable creation of multilingual screenshots and software videos. Workflows are captured once and reused across languages, reducing the need to recreate assets every time the UI or language changes.
What was previously repeated manual effort becomes a reusable foundation.
As software localization matures, the largest gains no longer come from optimizing translation alone. They come from removing the constraints that surround it.
By combining Transifex’s translation workflows with visual UI context from Rigi, teams remove one of the most persistent bottlenecks in software localization. Context is no longer something to explain, reconstruct, or chase down. It is part of the process.
The result is localization that scales with the product rather than slowing it down.