"DeepL calls its brand new Agent an AI-driven colleague. This assistant automates repetitive tasks, while the Customization Hub introduced today facilitates translation processes. In addition, DeepL has expanded its support with 70 new languages. DeepL Agent is available after extensive beta testing with more than 1,000 users. The tool performed 20,000 tasks during the test phase. The system automates tasks such as CRM management, customer service, and marketing activities, going far beyond the translation tasks you might associate with DeepL."
"CEO Jarek Kutylowski explains that customers often face the same challenge: "repetitive, disjointed tasks that reduce productivity." DeepL Agent tackles this by automating these routine processes. In doing so, DeepL is following the general trend of using AI to save time, but with a broad interpretation of what you can do with DeepL. The Agent works with existing systems such as CRM, email, and project management tools. According to DeepL, it understands a company's unique data and workflows."
"The Customization Hub brings glossaries, style rules, and translation memories together in one system. The platform automatically implements language requirements during the translation process. This minimizes errors and reduces the need for post-editing. Companies can thus maintain consistency in their brand voice and terminology. "By providing DeepL with the context of a language expert, companies can count on accurate translations, faster revisions, and fewer errors," according to the company."
DeepL launched an AI-driven Agent designed to automate repetitive and disjointed tasks across CRM, customer service, marketing, email, and project management. The Agent completed 20,000 tasks during beta with over 1,000 users and integrates with existing company systems while learning unique data and workflows. A Customization Hub centralizes glossaries, style rules, and translation memories to automatically apply language requirements, reduce errors, and minimize post-editing. The combined approach aims to speed localization, maintain brand voice and terminology consistency, and preserve human oversight for precision and control.
Read at Techzine Global
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