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ModelFront Demo - An example workflow with ModelFront
To accelerate a traditional fully manual post-editing workflow, an automatic quality prediction step is added before the manual human post-editing step.
ModelFront Demo - Hybrid translation workflow
Example of a hybrid translation workflow: 78% savings by skipping post-editing for all machine translations where the predicted quality is above 50%
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ModelFront Reviews (2)

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ModelFront Reviews (2)

5.0
2 reviews
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KA
Small-Business (50 or fewer emp.)
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"API simple access and huge language coverage"
What do you like best about ModelFront?

API access and language coverage, including those with exotic writing systems. Unlike translation providers like Microsoft or Google, ModelFront's quality prediction even has full support for customization for niche pairs like Armenian to Swahili.

Developer support has also been good, and Adam and the team can answer my questions as an NLP researcher. Review collected by and hosted on G2.com.

What do you dislike about ModelFront?

It's a bit expensive for the use cases I need Review collected by and hosted on G2.com.

Daniele G.
DG
Mid-Market (51-1000 emp.)
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"User-friendly MTQE for efficiency gains across the whole localization pipeline"
What do you like best about ModelFront?

A very accurate estimation of MT quality/risk. Aleady a first evaluation of 6 months post-editing data already allowed us to improve our efficiency while keeping the overall quality level. Easy to use, responsive, and compatible with the most-used data format. Review collected by and hosted on G2.com.

What do you dislike about ModelFront?

It's not yet available on some TMS's, so the evaluation process can be cumbersome. But I'm sure they are going to add integrations pretty soon (each TMS should offer this kind of integration actually!). Review collected by and hosted on G2.com.

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Machine Learning
Machine Translation
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ModelFront