Today’s web and mobile app localization industry relies on numerous standards, libraries and file formats to facilitate the exchange between developers and translators. While some formats are somewhat sophisticated, others lack even the most basic features, like pluralization and contextualization. And most can’t offer support for more advanced localization features, like language cases. The most common localization formats include Gettext PO, PHP Arrays, Android XML, YAML, .Net RESX, iOS Strings and many others. A typical developer today works with many frameworks - for instance a Laravel backend app (PHP Arrays) with Ember front end (i18n JS) and iOS mobile app (Strings). Since all standards have distinct syntax, in many cases translations cannot be shared across applications. Translation Markup Language (TML) aims to solve both these problems by introducing a powerful extensible cross-platform syntax that offers support for pluralization, language contextualization, language cases, reusable decorators and much more. TML libraries are available for all major web and mobile platforms. TML allows translators to do in-context translations - where they can translate right from within the apps. TML libraries also eliminate the need for developers to ever deal with the resource files, as all extractions and translation substitution is done realtime and the resource files are only used as a transport between the apps and the Translation Exchange platform. Translation Exchange stores all translations in Universal Translation Memory (UTM), a graph database which stores all translations with their context, tone, rank and other attributes for accurate matching. This allows translations to be shared across all apps in the Translation Exchange Network. The translation memories of each app are extracted from the UTM graph and are managed by their individual localization teams. During this presentation we will look at some of the features of TML and how it can be used to quickly translate a Ruby on Rails application into any number of languages using in-context translation tools. We will also look at how the data is stored and shared across applications using UTM.