An XLIFF editor lets you translate and review the bilingual segments inside an XLIFF file without touching its structure. Smartcat's Software Localization Agent imports XLIFF 1.2 and 2.0, shows source and target side by side with inline codes protected, leaves translate="no" units locked, and exports XLIFF 1.2 — the flavor most tools import cleanly.
Trusted by 1,000+ enterprise brands that translate XLIFF files in Smartcat
XLIFF exists to carry translations between systems, which is exactly why editing it casually goes wrong. Three things fail:
Inline codes get mangled — formatting and placeholders live inside segments as tags, and a generic editor or a raw machine-translation pass moves, drops or translates them. The re-import fails, or the bold lands on the wrong word in every slide.
Segment states vanish — the file tracks what is translated, reviewed and approved, and losing those states means a reviewer re-reads 4,000 segments to find the 200 that changed.
The round trip breaks silently — the file opens fine, translates fine, and then the receiving tool rejects it, or imports it with codes misplaced.
Anyone who has exported a Storyline course to XLIFF and gotten a broken file back knows this failure by heart.
Smartcat parses an XLIFF file into its translation units and presents each segment's source and target side by side.
This is XLIFF localization handled by the Software Localization Agent at parse level: Smartcat is fully compliant with the XLIFF 1.2 specification and adds only a few Smartcat-specific tag attributes to imported files.
1
Upload the XLIFF
Exported from your TMS, CMS or authoring tool, straight into the Software Localization Agent. No file conversion needed.
Smartcat accepts XLIFF 1.2 and 2.0 plus vendor flavors — SDLXLIFF, MQXLIFF, and XLIFF from Articulate Rise 360, Articulate Storyline and Easygenerator.
2
Choose how existing translations are handled
Lock imported translations and confirm them to the last stage, or leave them open for editing. Units marked translate="no" stay locked either way.
3
Translate and review
AI drafts unreviewed segments, translation memory fills what has been translated before, and the Tag Aligner places inline tags for you.
Source and target sit side by side for review, with your glossary applied.
4
Export and re-import
XLIFF 1.2, with the same unit IDs and structure, back into the system it came from.
Re-importing a file someone edited outside Smartcat? You choose "Update all segments" or "Skip segments changed in Smartcat".
Free for 15 days with 15,000 Smartwords and full access to translation capabilities, no credit card.
Upload one file from your own pipeline and run the loop end to end before you commit production work to it.
1.2 + 2.0
Imported
Import accepts both versions, plus vendor flavors: SDLXLIFF, MQXLIFF and XLIFF exports from Articulate Rise 360, Articulate Storyline and Easygenerator — which covers the classic L&D case of an authoring-tool course export.
Format support means your file will parse; it is not a guarantee about your whole pipeline.
1.2
Exported
Export is XLIFF 1.2 only, and deliberately so — 1.2 is the most stable flavor and the one most tools import without argument.
But the round trip is not symmetric: hand Smartcat a 2.0 file and you get 1.2 back. If your receiving system only ingests 2.0, this loop will not close — test one small file first.
280+
Languages
Translate XLIFF units into any supported pair, worldwide, with one translation memory and glossary across the project.
Stanley Black & Decker moved L&D content localization to Smartcat.
Smartcat’s AI translation is a fantastic tool. Our ability to source content from a central repository and benefit from adaptive algorithms which incorporate translation memories and glossaries across all project teams mean the business as a whole gains from each team’s translations.
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The export carries the same unit IDs and structure the file came in with — ID matching is what your re-import depends on.
Locked units stay locked, inline codes come back where they belong, and the file is spec-compliant XLIFF 1.2.
Smartcat's AI agents support over 80 file types, including Microsoft Office (.docx, .xlsx, .pptx), Adobe InDesign (.indd), PDFs, HTML, XML files, JSON, and subtitle files (.srt, .vtt).
This flexibility enables localization of business documents, multimedia assets, and eLearning content in one platform.
Translating other developer formats in the same project? JSON, XML and strings.xml, and YAML share the same translation memory and glossary. XLIFF is not the only bilingual format Smartcat handles: gettext PO files work the same way, with placeholders locked and revision history preserved across re-imports.
Unit IDs and source text
Translation-unit IDs are untouched, so re-import matches by ID, and the source text is never modified.
Inline tags, placed for you
Inline codes are protected, and the Tag Aligner reinserts them in the translated text automatically rather than leaving tag surgery to whoever is translating.
Locked units stay locked
Units marked translate="no" are locked in the editor regardless of the import options you choose, so approved content cannot be overwritten.
Pre-translated targets
Targets that arrive already filled in are kept, and can optionally be locked and confirmed to the last stage with the "Lock segments for imported translations" import option.
Re-import after outside edits
You choose "Update all segments" or "Skip segments changed in Smartcat". Pick deliberately: "Update all" overwrites edits made in Smartcat.
Where the Tag Aligner stops
Tag position is still a translation decision when word order inverts, so budget a review pass for it on high-visibility content.
Data security
Smartcat is SOC 2 Type II compliant. Files are encrypted in transit and at rest, workspaces are isolated and access is role-based — details on the security page.
Accepted XLIFF flavors
Plain 1.2 and 2.0, SDLXLIFF, MQXLIFF, and course exports from Articulate Rise 360, Articulate Storyline and Easygenerator — alongside 80+ other file types in the same project.
QA the export before re-import
To check the exported file outside Smartcat, our documentation recommends Verifika, Xbench, lexiQA or QA Distiller before you re-import.
Integrations and the CI/CD CLI keep recurring exports moving without manual hand-offs.
Upload the XLIFF, translate and review with locked units respected and inline codes protected, export valid XLIFF 1.2. Free for 15 days with 15,000 Smartwords, no credit card.
XLIFF is a bilingual exchange format: it separates the translatable text into segments and carries formatting and placeholders as inline elements, so translation happens without editing the file's structure.
XLIFF localization is the loop of exporting that file from the system that owns the content, translating and reviewing the segments, and re-importing the result by unit ID.
L&D teams get XLIFF out of their authoring tool — Rise 360, Storyline, Easygenerator — and that is exactly what this workflow takes.
The alternative is retyping course text into a translator and rebuilding the course by hand. Smartcat's Learning Content Agent and Software Localization Agent handle the same content inside one project.
The file is parsed into its translation units and shown source-beside-target.
Export is XLIFF 1.2 with the same unit IDs and structure, ready for re-import into the originating system.
One direction only. Import accepts 1.2 and 2.0; export produces XLIFF 1.2 — so a 2.0 file effectively comes back as 1.2, and there is no 1.2 to 2.0 conversion.
If your receiving system requires 2.0, convert after export with an external tool, or keep that file out of this workflow.
XLIFF 2.0 introduces a more modular architecture with a streamlined core and specialized extensions for advanced functionality.
Compared with 1.2 it offers better handling of inline elements, richer metadata support, and stronger validation.
For one-off edits outside a translation workflow, Smartcat's own documentation recommends the desktop editors Poedit (2.2 or later) and Virtaal.
The workflow on this page — translation memory, glossary, review stages, locked-segment handling, round-trip at volume — is what teams use when XLIFF is a recurring pipeline rather than a single file.
No — translate="no" units cannot be overwritten.
Vendor-supplied partial files are the case this is built for.
Smartcat is SOC 2 Type II compliant. Your XLIFF files are encrypted in transit and at rest, workspaces are isolated, and access is role-based.
Re-import the exported XLIFF into the system that generated it — the round trip is ID-matched.
If you need the final document itself, such as a DOCX or a course package, that merge happens in the originating tool rather than in the editor.
Smartcat's general ceiling for project files is 6 GB, and the docs advise splitting anything over 1 GB for speed; no XLIFF-specific segment-count limit is documented.
On file count there is no cap — batch uploads of hundreds of files into one project are supported, so a full course export goes in as one job.
Neither limit varies by plan: tiers differ on integrations and Marketplace billing, not on uploads. The constraint is per-file size, not file count.
Inline elements represent formatting, placeholders and other non-translatable content inside a segment. They are protected during translation, and the Tag Aligner reinserts them in the target automatically.
Two limits worth knowing: tagless editing is unavailable for Chinese, Japanese and Korean, and tags are forced visible on any segment where a quality check flags an alignment problem.
Not covered here? Book a demo — a 1:1 with a localization engineer, no commitment.
Usually — and there are two things worth checking before production work depends on it.
Unit IDs and structure are preserved either way, which is what ID-matched re-import actually depends on.
For any system not on the documented list, run one small file through the full loop first — sound practice with any XLIFF tool, including ours.
1. Paul, C., Smith, K., Taylor, B., & Underwood, G. (2025). The future of AI in corporate training: Opportunities and challenges [Preprint]. ResearchGate.
2. Al Naqbi, H., Bahroun, Z., & Ahmed, V. (2024). Enhancing Work Productivity through Generative Artificial Intelligence: A Comprehensive Literature Review. Sustainability, 16(3), 1166.