If there is one constant in our industry, it’s the conversations about quality. Our shared goals are to make sure that everyone can consume content in their own native language. And to do that well, quality is of the utmost importance.
However, the large volumes of content waiting to be translated, faster than ever and with lower budgets has become a constant challenge in delivering the right quality. How do you measure quality efficiently, at scale, and without costly and time-consuming human effort?
TAUS brings you EPIC: our next-generation API that brings together Quality Estimation (QE) and Automatic Post-Editing (APE) in a single solution.
The days of machine translation when all output needed human review, and amusing (yet reputation damaging) errors were in abundance, are behind us.
Machine translation is better than ever and for certain domains and languages, publishing raw MT is no longer a crazy thought. Those still sending all of their machine translated segments for human review are throwing money (and time) out the window.
Half of the money you spend on your translations is wasted, but the trouble is you don’t know which half. What if you could instantly know which translations are ready to go, and which need improvement? This is exactly where EPIC comes in.
EPIC is not just another quality control tool. It’s an AI-powered companion – designed to work alongside human experts and enhance productivity, rather than replacing people.
Here’s what makes EPIC stand out:
One of the biggest challenges in adopting Quality Estimation is the “replacement trap.” Many fear that AI-driven quality tools will replace human linguists and quality assessors, leading to skepticism and resistance. But the truth is quite the opposite.
For model trainers, the trap lies in over-engineering QE models by spending excessive time collecting vast amounts of human LQA data, aiming to replace human evaluation entirely. But QE isn’t meant to replicate human judgment. It’s designed to provide fast, consistent, and scalable quality assessment that complements human expertise.
For users such as QA managers and linguists, the misconception is that QE models will take over their role. But in reality, humans struggle with selective attention and cognitive biases, often leading to inconsistent assessments. QE models, on the other hand, process vast amounts of translations quickly and highlight the most critical quality issues. They don’t replace human reviewers; they help you focus on the nuanced, complex errors that truly require human expertise. By leveraging EPIC, businesses can handle 10 - 100 times more content while maintaining high-quality output.
As machine translation and large language models continue to advance, Quality Estimation is becoming a must-have rather than a luxury. The industry needs solutions that are fast, scalable and reliable. And that’s exactly what EPIC delivers.
EPIC is more than just an AI tool. It’s Your AI Quality Companion. We believe in the power of EPIC to transform your translation workflows.
Anne-Maj van der Meer is a marketing professional with over 10 years of experience in event organization and management. She has a BA in English Language and Culture from the University of Amsterdam and a specialization in Creative Writing from Harvard University. Before her position at TAUS, she was a teacher at primary schools in regular as well as special needs education. Anne-Maj started her career at TAUS in 2009 as the first TAUS employee where she became a jack of all trades, taking care of bookkeeping and accounting as well as creating and managing the website and customer services. For the past 5 years, she works in the capacity of Events Director, chief content editor and designer of publications. Anne-Maj has helped in the organization of more than 35 LocWorld conferences, where she takes care of the program for the TAUS track and hosts and moderates these sessions.