Burcu Uluçay
AI translation
Blog
Notes on language, technology, and reaching a global audience.
If traditional dubbing is straining your budget, multiagent AI is the alternative
Traditional dubbing creates a challenging equation for content owners: complex logistics, extended timelines, and significant costs per finished hour…
Localization projects fail, here's why and how agentic AI solves it
Content owners and streaming platforms need accessible, culturally accurate content across global markets. Most struggle with speed, quality, and cost…
AI translation technology comparison: NMT, LLMs, and Agentic systems
Companies expanding globally face a translation dilemma. Manual translation takes too long and costs too much for the volume of content they need to…
How to Choose the Right AI Translation Technology for Audiovisual Content?
Only 1% of "useful content generated every day" gets translated, according to CSA Insights' analysis. For video content, that percentage is likely even…
AI Video Translation - Multiagent Systems Solve Quality & Cost Issues
Video translation projects hold enormous potential for global reach, yet they consistently derail from budget and cause delays because standard AI systems…
Standard vs Generative vs Multiagent AI: Which Delivers Better Translation Results?
Most translation projects fail because companies choose AI technology based on marketing promises rather than actual performance requirements. The…
Multiagent AI Solves Video Translation Challenges for Businesses and Media Companies
Content owners and distributors face persistent challenges with video translation despite significant investment. They struggle with scattered workflows…
Agentic AI in Translation: Highest Accuracy for Closed Captions and Subtitles across APAC
Agentic AI provides the necessary accuracy for demanding video captioning and subtitling workflows. The system, made up of multi agents, moves beyond…
What You Need to Know About Europe's Accessibility Rules for Captions and Subtitles
Neural Machine Translation (NMT) and Large Language Models (LLMs) promised automation for captioning, but have failed where it matters most: capturing the…
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