New Image Translation Feature! Localize Visuals at Scale Without Design Bottlenecks

Smartcat has introduced a new AI-driven image localization capability aimed at removing a major bottleneck in global content operations: translating visual assets without relying on design teams.

The release targets both marketing and learning & development (L&D) teams, where image-based content—such as campaign banners and eLearning visuals—has traditionally required manual redesign, slowing launches and increasing costs.

For enterprise teams operating across markets, image localization has long been slow and fragmented. Translating visuals often requires reopening files in tools like Adobe Photoshop, Adobe Illustrator, or Figma—or recreating assets entirely when only flattened formats are available.

Each update triggers design requests, back-and-forth workflows, and post-production fixes due to layout issues, font mismatches, or text expansion.

Smartcat’s new capability now automates the entire process.

Users upload images (PNG, JPEG, or exports), review translations in a structured interface, and download production-ready assets. The platform detects and translates text while preserving layout, fonts, and formatting—making outputs immediately usable.

For marketing teams, the impact is operational speed.

By integrating image localization into the same workflow as other content, Smartcat removes the need for separate design cycles. Campaign assets can be translated and deployed across multiple markets simultaneously, reducing delays tied to localization.

“Global images should be localized, not left in English,” the company notes, emphasizing the growing expectation for fully localized customer experiences.

The platform also applies translation memory and glossaries automatically, ensuring consistent terminology across all visual assets without requiring manual checks.

The implications are equally significant for L&D teams, particularly those managing multilingual eLearning programs.

Traditional localization tools often fail to handle images embedded within courses—such as screenshots, diagrams, and infographics—forcing teams to recreate visuals manually in each language. This is especially problematic in tools like Articulate Storyline and Articulate Rise, where visual elements are deeply integrated into course structure.

Smartcat addresses this by automatically identifying and translating text within embedded images when a course file (e.g., SCORM package) is uploaded. The platform then repackages the course with all visuals localized and ready for deployment in a learning management system.

The new functionality is powered by Smartcat’s broader AI enterprise platform, which combines machine learning with human-in-the-loop workflows.

Key components include:

• Continuous learning from subject matter expert edits

• Automated workflow orchestration across teams

• Integrated collaboration between AI and human reviewers

• End-to-end visibility across languages and projects

This approach allows organizations to scale content production globally without increasing headcount or relying on external agencies.

As enterprises expand into new markets, the demand for fully localized content—across both text and visuals—is increasing. Smartcat’s latest release reflects a broader shift toward unified content workflows, where localization is embedded directly into production rather than treated as a downstream task.

By removing design dependencies from image translation, the company positions itself to address a critical gap in global content operations—one that has historically slowed both marketing campaigns and training rollouts.