Real-time QE scores for your translation workflow
Real-time QE scores per segment via REST API — MQM, BLEU and TER compatible. Human post-editing lands where it counts: significant QA savings on large volumes.
Real-time quality estimation per segment via REST API: high-risk sentences are flagged for human post-editing on the spot, safe segments pass through untouched. MQM, BLEU and TER compatible.
QE is not a replacement for human quality control — it is a smart way to deploy that control where it counts. By routing low-quality segments straight to post-editing and processing high-quality segments faster, you raise the efficiency of your entire translation process. Our clients achieve significant QA cost savings — without compromising publication quality.
From core language combinations to low-resource markets — every language pair gets its own QE scoring profile.
You deliver source segments and machine translation output via API, file or our platform. Integration with mainstream TMS solutions (Trados, memoQ, XTM, Phrase) is supported as standard.
Our QE model analyses every translated segment and calculates a quality score based on metric (MQM/BLEU/TER) and linguistic parameters — without any reference translation.
Segments are ranked by quality score. High-risk segments that require human post-editing are identified upfront with an explicit risk indicator.
Only the lowest-scoring segments are routed to a native post-editor. That cuts QA cost significantly with no loss of publication quality.
You receive a complete quality report: per-segment scores, aggregate statistics, deviation patterns per engine and recommendations for further workflow optimisation.
Without quality estimation, your post-editors review every single MT segment — or guess where the errors hide. QE assigns a hard score per segment, so human time lands on the segments that genuinely deserve it. No shift in quality, but a meaningful shift in cost — and a faster path to publication.
Predictive quality scores so human expertise lands exactly where it should — without any reference translation.
Through our REST API you receive real-time QE scores per segment — directly usable in automated translation workflows and TMS integrations.
By post-editing only the low-scoring segments by hand, you cut post-editing and QA cost significantly — without sacrificing publication quality.
We support the industry-standard quality metrics MQM, BLEU and TER for full compatibility with your existing QA processes and reporting.
QE available for 225+ language combinations via REST API — direct integration into your translation pipeline, TMS or automated content workflow.
From MQM to REST API — the foundation of a translation workflow that decides on data.
From e-commerce pipelines and SaaS localisation to large-scale technical documentation.
E-commerce · Marketplace A marketplace processes 2M words of MT per month into 14 languages. With QE, high-scoring segments are published directly; only low-scoring segments go to a post-editor. Significant cost reduction.
SaaS · Localisation A SaaS provider with 85k UI strings in 20 languages. QE detects strings with high UI-break risk; only those go to human QA. Release cycle cut in half.
Industry · Tech docs An industrial manufacturer keeps technical documentation translated into 18 languages on a rolling basis. QE decides per segment which MT output is publication-ready and which must go back to a specialist. Lead time down 60%.
QE shines on high-volume MT output — from e-commerce to software localisation and technical documentation.
What clients say about working with Ecrivus — from marketplace MT pipelines to SaaS localisation.
Certified translations for our international cases are delivered quickly and carefully. Our project manager knows our account inside out.
No-obligation — response within one hour on business days
Below you'll find adjacent services, sectors we translate for often, and the most requested language pairs.
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Sectors we deliver this service for regularly.
Most requested combinations for this service.
Last updated: May 2026
