According to a recent LinkedIn post from Smartcat, the company is emphasizing image translation as a persistent gap in many localization workflows, compared with more mature tooling for text. The post highlights a proprietary “Image Translation 2.0” engine that is described as generating production-ready localized images while preserving fonts, layouts, and visual quality.
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The LinkedIn post suggests that this offering could significantly reduce manual design work by eliminating the need for designer involvement in localizing banners, ad creatives, and course graphics. It also underscores potential efficiency gains from easier scaling into more languages and simplified reviewer control, which may strengthen Smartcat’s value proposition for marketing and learning & development teams.
By pointing to end-to-end SCORM course localization, the post implies a focus on e-learning content and corporate training, segments that have been expanding with global digital adoption. For investors, this move could indicate Smartcat’s intent to deepen its differentiation in AI-driven localization and automation, potentially enhancing customer retention and opening additional revenue opportunities in high-volume, design-heavy content categories.
The emphasis on proprietary AI capabilities and workflow automation may also position Smartcat more competitively against other localization and translation management platforms. If adoption of the image translation tool scales as suggested, it could improve the company’s operating leverage by enabling customers to handle larger localization volumes without proportional increases in headcount or external design spend.