Traditional LQA is Slow and Expensive 
Because it requires skilled experts, many organizations only use human LQA selectively, due to the high costs and time involved.

Auto LQA Solves This
By automating the process with AI, Auto LQA offers a faster, more affordable way to manage LQA. You can now apply LQA to more content without losing quality or accuracy.

AI with Human Validation
Auto LQA produces high quality outputs, which can then be validated or edited by a human expert. This blend of AI-driven workflow and human oversight ensures accuracy, and can reduce LQA costs by up to 65% and cut processing time by as much as 99%.

Already Using Human-Led LQA? Adding Auto LQA is Easy

Just like using automatic pre-translation before a human translator starts working, Auto LQA takes care of the initial quality check. Your linguists can then focus on refining and validating the results, saving time and effort.

Upgrade Your Workflow with Auto LQA

Auto LQA opens up cost-effective ways to assess quality at scale. Use it to automate vendor evaluations or regularly assess translation quality without the need for human input.

“Auto LQA with Validation Mode will be a useful aid for human reviewers, helping them identify issues and making the LQA process less painful, as Auto LQA handles part of the workload. It will definitely help reduce turnaround time.”

Phrase customer in the medical information space

Here to field your questions

1. How is Auto LQA Priced?

Auto LQA is available for all plans above the Team or Professional level. It uses AI units included in your subscription, which you can top up when needed. For more details, click here.

2. What Makes Auto LQA Different from the Quality Performance Score (QPS)?

Both features use AI to assess quality, but they serve different purposes. QPS is designed to give you a simple, easily understood score. Auto LQA goes further, by applying the MQM framework, assigning error categories (like accuracy or style) and severity levels (from minor to critical). It also provides a text description to clearly explain the error.

You can use these two features together. For example, run QPS at the job level, then use Auto LQA for jobs that score below a set threshold. Segments with issues can be sent to a linguist for review, while the rest are locked.