Announcing Humlens: AI localization for text, video, image, and audio

Most teams don't localize with one tool. They localize with five — a translation management system for strings, a separate vendor for subtitles, a freelancer for dubbing scripts, an image editor for on-image text, and a spreadsheet to track all of it. Every format has its own workflow, its own reviewers, and its own way of quietly falling out of sync with the source content.

Humlens is our answer to that: one workspace that handles text, video, image, and audio localization with AI translation up front and human review built in, instead of bolted on.

What that looks like in practice

Text. Import JSON, YAML, PO, XLIFF, ARB, and other structured formats, translate with AI, and export back into the same structure your codebase already expects — no hand-editing files to fix broken keys.

Video. Translate subtitle and caption tracks, validate timing against the original display window before a translated line ever reaches post-production, and generate dubbing scripts adapted for lip-sync pacing rather than a flat word-for-word translation.

Image. Localize on-image text and flag cultural color and iconography choices that don't travel well across markets, instead of leaving that judgment to whoever happens to be reviewing the export.

Audio. Apply the same translate-then-review workflow to podcasts, IVR prompts, and e-learning narration, where timing and tone matter as much as accuracy.

Why we built it this way

AI translation is fast enough now that speed isn't the bottleneck. Trust is. A translation that's 95% right but silently wrong in a customer-facing string, a subtitle that overflows its display window, or a dubbing script that ignores lip-sync timing — those are the failures that actually cost teams time, because someone has to catch them after the fact.

So Humlens treats AI translation as a first draft, not a final answer. Every format runs through the same shape of workflow: translate, validate against format-specific constraints (timing, structure, length), then route to a human reviewer with an approval gate before anything ships. The AI does the first 90%; the workflow makes sure a person signs off on the last 10% that actually matters.

What's next

This blog is where we'll write about the parts of localization that don't fit in a feature list — how we think about subtitle timing, why dubbing scripts need their own pacing model, what it actually takes to localize twenty different file formats without breaking any of them. If you're localizing a product right now, we'd like to hear what's slowing you down.

Start free or book a demo to see it on your own content.