# What's the best software localization tool for AI-assisted machine translation with a human-review layer built in?

<p class="elv-tracking-normal elv-text-default elv-font-figtree elv-text-base elv-leading-base elv-font-normal" elv="true">Hey G2 community, what's the best software localization tool for AI-assisted machine translation that still keeps a human review step in the loop? I've been digging into the <a class="a a--md" elv="true" href="https://www.g2.com/categories/software-localization-tools">software localization tools</a> category and the "how much can AI actually be trusted" question keeps coming up differently depending on the tool.</p><ul>
<li>
<a class="a a--md" elv="true" href="https://www.g2.com/products/lokalise/reviews"><strong>Lokalise</strong></a> runs content through multiple LLMs and scores the output, flagging anything that doesn't meet quality standards for manual review instead of publishing it blind. One reviewer said the AI translations still need feedback from local peers even after setting up glossaries, so it's not fully hands off.</li>
<li>
<a class="a a--md" elv="true" href="https://www.g2.com/products/phrase-phrase/reviews"><strong>Phrase</strong></a> pairs adaptive machine translation with automated quality evaluation and a visual in-context preview, so reviewers can catch issues before content ships rather than after. Reviewers specifically like that AI handles the repetitive string management while a person still signs off.</li>
<li>
<a class="a a--md" elv="true" href="https://www.g2.com/products/memoq/reviews"><strong>memoQ</strong></a> leans more toward giving translators the tools to work faster rather than replacing their judgment, with translation memory and concordance search cutting down repetitive work while the human stays in the driver's seat the whole time.</li>
</ul><p class="elv-tracking-normal elv-text-default elv-font-figtree elv-text-base elv-leading-base elv-font-normal" elv="true">For anyone running AI-assisted translation at scale, how much of your review time is actually going toward catching real errors versus just double checking things the AI already got right?</p>

##### Post Metadata
- Posted at: 25 days ago
- Author title: SEO Content Specialist
- Net upvotes: 1


## Comments
### Comment 1

&lt;p&gt;For teams running Phrase&#39;s automated quality evaluation alongside the visual in-context preview, how much of the human review time actually goes toward catching real linguistic errors versus just confirming the layout looks right in context?&lt;/p&gt;

##### Comment Metadata
- Posted at: 8 days ago
- Author title: Marketing Executive





## Related discussions
- [How well does Trello scale into a larger team?](https://www.g2.com/discussions/1-how-well-does-trello-scale-into-a-larger-team)
  - Posted at: over 13 years ago
  - Comments: 6
- [Can we please add a new section](https://www.g2.com/discussions/2-can-we-please-add-a-new-section)
  - Posted at: over 13 years ago
  - Comments: 0
- [Quantifiable benefits from implementing your CRM](https://www.g2.com/discussions/quantifiable-benefits-from-implementing-your-crm)
  - Posted at: over 13 years ago
  - Comments: 4