February 2026 Summaries

As global businesses face an overwhelming surge in translation needs, outdated translation processes are causing significant operational bottlenecks, with delays and rising costs impacting product launches and brand consistency. Many organizations still rely on manual translation processes or legacy systems, which cannot scale with the increasing demand for multilingual content. The transformative potential of AI in translation is highlighted as a solution, offering instant, high-quality translations, customizing them for business needs, and ensuring quality and compliance from the outset. AI enables seamless translation across various formats, reducing human error and accelerating delivery while adhering to stringent security and compliance standards. Embracing AI's role in orchestrating the entire translation process can significantly enhance efficiency, allowing businesses to maintain speed, scale, and quality without compromising strategic priorities.

DeepL Agent is an AI tool designed to streamline the process of handling returns, refunds, and exchanges for customer service teams by automating complex workflows without the need for coding or system integrations. Unlike traditional chatbots, DeepL Agent can reason, plan, and execute tasks across various systems by using a browser interface, making it compatible with proprietary tools that lack APIs. By navigating tools like customer support platforms and billing systems, it verifies account details, validates refund eligibility, and processes cancellations, all while ensuring clear communication with customers. With enterprise-grade security and compliance, including adherence to EU AI Act and ISO 27001 standards, DeepL Agent allows customer service teams to manage high volumes of requests efficiently, deploying sub-agents to handle multiple tickets simultaneously, thus reducing strain and enhancing focus on customer interactions that require empathy and trust-building. This innovation not only speeds up resolutions but also allows teams to scale operations without increasing headcount, ensuring accuracy through reviews at critical stages and safeguarding sensitive data.

DeepL is positioned as a distinguished AI company with a focus on long-term growth and sustainability through innovative technology, financial discipline, and global ambition. Under the leadership of CFO Martino Cadoni, who has a track record of scaling businesses, DeepL emphasizes the importance of building proprietary AI models and maintaining end-to-end control over its technology stack to ensure quality, accuracy, and trust. The company's strategy involves disciplined capital allocation and investment in research, talent, and infrastructure to reinforce its unique position in the market. As DeepL expands its reach across various enterprise sectors and geographies, it prioritizes responsible scaling and maintaining strong customer relationships. DeepL's approach aims to create sustainable value by focusing on quality and trust rather than short-term growth metrics, with an understanding that AI companies require distinct financial strategies due to the capital-intensive nature of the industry.

DeepL Agent is an AI tool designed to enhance customer service operations by automating complex workflows and reducing the need for human intervention in routine tasks. It allows customer service representatives to focus on more meaningful interactions by handling tasks such as navigating systems, gathering necessary information, and monitoring updates across different platforms—all without requiring coding or complex integrations. This AI agent supports multilingual communication and can manage tasks like knowledge management, quality assurance, and sentiment analysis, ensuring a more efficient and seamless customer experience. By reducing the time spent on repetitive tasks, DeepL Agent empowers teams to concentrate on building stronger customer relationships, ultimately boosting productivity without increasing headcount.

AI adoption in the legal sector has rapidly transformed workflows and business models, as evidenced by a 2025 survey conducted by DeepL, revealing that 96% of legal professionals in the U.S. now utilize AI, with 77% having increased their AI spending. This swift integration, however, has led to unauthorized use of AI tools by 71% of professionals, highlighting a lack of formal approval processes and raising concerns about security, compliance, and the quality of legal advice. To address these challenges, legal organizations must develop robust AI strategies that balance innovation with compliance, using approved platforms that meet security and accuracy standards. DeepL emphasizes the importance of selecting AI partners who are committed to both product development and compliance, offering tools like customized multilingual AI solutions that align with legal requirements. By focusing on strategic AI adoption, legal teams can enhance their expertise, ensure compliance, and achieve tangible returns on investment, thereby transforming their operations and client interactions while mitigating risks associated with shadow AI usage.

DeepL Voice API offers a transformative solution for contact centers and Business Process Outsourcing (BPO) firms by providing real-time transcription and translation, allowing agents to communicate effectively with customers regardless of language barriers. This technology enables seamless multilingual support, reducing call transfers and enhancing problem resolution speed by keeping interactions with the initial agent. It benefits various roles within an organization, such as BPO Program Directors, Contact Center Operations Leaders, Quality Assurance Managers, and Training and Enablement Leads by standardizing quality, optimizing call routing, and facilitating faster onboarding and training. Unlike other solutions, DeepL Voice API combines speed and accuracy in a single, real-time workflow without compromising data security. The upcoming feature of voice-to-voice translation promises further improvements by allowing agents to hear translations in real time, which is crucial for handling urgent or emotional calls.