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Making LLMs work for scalable, brand-consistent multilingual content

Join Phrase for a webinar tailored to localization leaders looking to harness large language models (LLMs) safely, at scale, and in line with brand standards. Learn how LLMs are evolving from experimental tools into production-ready engines for generating, adapting, and evaluating multilingual content across the localization workflow.

A defining moment for localization technology

As AI rapidly evolves, so do the opportunities, and the risks. In this session we share how localization professionals can move from experimentation to operationalization. We examine the pivotal role of LLMs in scaling personalization, improving governance, and transforming localization into a strategic business function.

We break down the core capabilities that make AI operational in a localization context, structured around three key pillars:

  • Generate: Efficiently produce multilingual content with fluency and speed
  • Adapt: Fine-tune translations to match brand tone, voice, and regulatory context
  • Evaluate: Ensure quality and control with AI-assisted review and scoring

See how Phrase is putting LLMs to work across the entire localization pipeline. We demo our latest innovations including a sneak peek at what’s coming next on the roadmap: 

  • Phrase Next GenMT: Multi-segment MT for improved contextual fluency
  • DeepL Next-Gen & Widn.AI: Integrations built for scale and nuanced translation
  • Auto Adapt: Customizing translations to match tone, voice, and brand style
  • MT Optimize: Tuned output for enhanced relevance and precision
  • Use cases: Example applications in high-volume content operations

 

Speakers:

  • Semih Altinay, VP AI Solutions at Phrase
  • Miklós Urbán, Principal Enterprise AI & Automation Architect at Phrase