What advantages does Verify have over traditional translation workflows?
Most teams still move multilingual content through a relay race of emails, platforms, and per-word quotes – which is why launches slip, costs creep, and quality varies by whichever translator picked up the brief that week.
If you’re hearing about Verify for the first time, here are the simple reasons people compare it to their traditional workflow:
It gives you a measurable score of translation quality, is a faster path to publish, and loops in human expertise only where it’s needed.
Here’s what you get with Verify
Know when it’s “good enough.” You can choose to use Quality Evaluation to get a quality score for each file, helping you decide what to publish confidently and what to escalate for human review.
Set and forget automation. Orchestrate – a visual, no-code builder inside Verify – routes content by quality score, language or content type, removing the need for manual hand-offs, and making workflows a breeze.
Review together, not by email. Verify’s Collaborate feature lets internal and external teams edit and review content in one platform, no email threads, no strings of technology to push your content through.
Keeps sensitive drafts private. Verify runs on a closed-loop ISO 27001 certified AI stack hosted by Straker, so your content isn’t leaked to public AI models.
Slots into the way you work today. Integrations with Slack, Microsoft Teams, PowerAutomate and others mean you can harness the power of Verify without disrupting your existing ways of working.
Why this matters now
AI use has gone mainstream – McKinsey reports78% of organisations used AI in at least one function last year, with 71% regularly using generative AI.
The leaders aren’t just “adding AI”; they’re rewiring workflows around it.
Traditional, human-only pipelines can’t keep pace with that shift: they’re slow, expensive, and inconsistent – and they provide no objective read on AI output.
Dimension
Traditional workflow
Verify
Speed to publish
Linear hand-offs; queues and re-reviews stretch timelines.
AI translate → instant quality score; only low-confidence segments go to humans.
Cost model
Mostly per-word (plus rush fees for tight deadlines).
Usage-based AI tokens; spend human verification only where needed.
Quality visibility
No objective, pre-publish quality signal. (Relies on reviewer judgment.)
Built-in quality evaluation on every file/segment.
Human involvement
Blanket human review across whole files to manage risk.
Targeted human verification triggered by rules/thresholds.
Automation
Email and portal steps; manual routing and follow-ups.
Traditional multilingual-content workflows depend on people for every step, which creates delays, variability, and hidden coordination costs – from timezone waits to quote negotiations and re-reviews.
Verify blends AI speed with human oversight and, crucially, tells you how good the output is before you publish.
That addresses two of the biggest objections to AI that teams raise internally: “Can we trust the quality?” and “Will we still be in control?”
What doesn’t change
You still set the bar for quality and who signs off. You still apply brand terminology and style – only now those decisions are clearer and faster to execute. If you need a human specialist, it's just a click, not a new project.
Want to take a look?
If your current process is slow, expensive, and inconsistent – and gives you no objective read on AI output – you’re exactly who Verify was built for. It gives you quality you can measure, automation you can trust, and human expertise precisely where it pays back.
Book a demo to see how Verify works for your multilingual business.