Lilt is an AI-powered language service provider (LSP). Lilt combines adaptive neural machine translation technology, an enterprise translation management system, and professional translators to allow organizations to scale their translation programs and improve the global customer experience. They purport to improve translation speed by 3-5x and reduce costs by 50% or more. Lilt HQ is based in San Francisco and is backed by VCs like Intel Capital, Sequoia, Redpoint, Zetta, and…
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Wordbee
Score6 out of 10
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Wordbee in Luxembourg offers their eponymous computer-assisted translation and translation management.
Lilt is a great platform for translating and reviewing content for mainstream languages that are spoken by a large number of people such as Spanish, French, etc. in which case the machine translation tool does a great job of adding the appropriate fluency, grammar, and punctuations. The QA checks also likewise provide apt feedback with rarely any errors. The only shortfall for Lilt is when the content to be translated belongs to any non-mainstream languages (such as regional Indian state ones) and the most noticeable errors are thrown by the QA check tools which have several long-standing unfixed bugs.
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
It is easy to view two columns of source and target, and when using the filter to see just untranslated segments. TM and matches can be seen and differentiated easily. Scenarios where it is less appropriate are their spellcheck and filter areas, which could be improved by adding more options.
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
Different colors to differentiate the status of the segment. One can click on the segment and change the color for the segments that were translated and those that still need to be reviewed.
Machine translation interface. There are three different machine translators at the side of the segments.
TM can be seen with matches highlighted at the side.
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
Find and replace option could be improved to be easier.
The filter could have more options.
Spellcheck and QA need to be improved because I can not see it as an option in the online interface of my client. I need to download the document to do the spell check, and then correct the errors with the find and replace option.
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
