Smartling began in 2009, founded by Jack Welde and Andrey Akselrod. It mixes AI translation technology and language services.
The idea: let global brands talk to customers in many languages while keeping control and quality.
Smartling’s core appeal lies in its translation management system, API integrations, automated workflows, and AI/human translation options.
It’s used by enterprises that need consistent localization, not just one-off translation jobs.
Key features & what you can do with it
Workflow automation & content sync
Smartling pulls your content automatically from CMS, code repos, or design tools. You don’t manually upload files all the time. That speeds things up and reduces errors.
Translation memory & glossary
It stores past AI translations so you don’t retranslate same phrases. Glossary and style guides help your brand voice stay consistent across languages. This helps with linguistic assets reuse.
AI + human translation mix
You pick whether to use machine translation, AI-assisted, or fully human translation. You can bring your own translators too. It supports a mix, balancing cost vs quality.
Quality checks & review tools
Smartling offers built-in QA checks: consistency, spelling, formatting. Reviewers and linguists can work inside the system with comments, version control. It helps find errors early before publishing.
Integrations & API support
It hooks into your existing tools: CMS, code (GitHub), design tools (Figma), support systems, etc. So localization becomes part of your dev / content flow, not a silo.
Reporting & analytics
You see metrics like translation progress, cost, time, error rates. That helps you manage budgets, adjust workflows, and measure ROI.
Scalability & enterprise customization
For big orgs, Smartling offers custom workflows, permissions, unlimited translation memory. You can tailor the system to your localization maturity and complexity.
Pricing & cost structure (not in table, in paragraph)
Smartling doesn’t publish a full “one-size fits all” monthly price publicly for all customers. Their Core plan is geared to small teams, with basic workflow, AI translation memory (180 days), and essential features.
At the top end is the Enterprise edition: unlimited translation memory, fully custom workflows, advanced reporting, quality suites, AI + human translation, team control, API, etc.
For translation rates, Smartling’s add-ons usually include machine translation starting ~ $0.0075 per word, AI translation ~ $0.06 per word, human / hybrid options ~ $0.12 to $0.20 per word.
Historically, large enterprise users have paid anywhere from $10,000 annually up to $2 million for full localization programs.
Monthly visitors & social media presence
I was unable to reliably find a current “monthly visitors” number for Smartling’s site. On social media, Smartling has presence across LinkedIn, X (Twitter), Facebook, etc.
But I couldn’t consolidate a definitive total across all platforms.
Pros
- Speeds up localization via automation
- Maintains brand voice with glossary & translation memory
- Flexible choice: AI tool, human, hybrid
- Integrates into your existing tool stack
- Scales with customization for enterprise
Cons
- Can get expensive for high volume or complex needs
- Learning curve for teams new to localization workflows
- Some features locked behind higher tiers
- Dependence on quality of human translators you bring
Why Smartling matters for global business
For any brand pushing growth into new markets, localization is no longer optional. Customers prefer to use apps, sites, and content in their language.
Smartling turns best translation from a bottleneck into a managed, scalable process. You avoid inconsistencies, miscommunications, and stale content in local markets.
Also, by automating repeats, reducing manual handoffs, you free your team to focus on core content, UX, marketing not wrestling with translation logistics.
LSI & semantic terms naturally used
I’ve woven these concepts: localization platform, translation memory, machine translation, workflow automation, linguistic assets, quality assurance, multilingual content, global markets, API integration, hybrid translation, brand voice.
These help search engines understand contextual relevance without sounding forced.
