Choosing an enterprise translation platform is a strategic decision that powers a company’s global growth. The right platform can accelerate market entry, enhance brand consistency, and create a scalable foundation for international operations. The wrong one can introduce friction, inflate costs, and hinder expansion.
In the localization market, two prominent names often surface: Smartling, an established and powerful cloud translation management system, and Translated, a pioneering, AI-first language platform using a powerful combination of expert human translators and machine intelligence. While both offer solutions for managing multilingual content, they represent fundamentally different philosophies. This decision is a choice between a traditional system and a self-improving, AI-powered ecosystem built for innovation. This Translated vs Smartling comparison will explore the critical differences to help you determine which partner is right for your global journey.
Platform capabilities comparison
Core philosophy: management vs. innovation
Smartling provides a strong, feature-rich platform designed to give enterprises control over complex localization workflows. This approach excels at bringing order to multifaceted projects, making it a strong solution for companies seeking to manage and streamline existing, often intricate, translation supply chains.
Translated operates on a philosophy of innovation centered on Human-AI Symbiosis. The goal is to make translation fundamentally better, faster, and more efficient with every project. The platform, TranslationOS, is designed to facilitate a virtuous cycle where professional translators continuously train a purpose-built AI, Lara. This creates a compounding return on investment as the system becomes a more intelligent language asset for the organization over time.
The role of AI in each platform
Smartling integrates AI primarily for automation and quality assurance. It uses artificial intelligence to streamline workflows, automate quality checks, and reduce manual project management tasks. The AI serves as a powerful assistant to the traditional translation process.
In Translated’s ecosystem, AI is the core of the translation process itself. Lara, our proprietary, context-aware large language model, is not a generic AI retrofitted for translation; it was built specifically for this purpose. It learns in real-time from the feedback of professional linguists, ensuring that every correction and stylistic refinement improves its future performance. This adaptive learning model, combined with its ability to process full-document context, delivers translations that are not only accurate but also fluent and consistent.
Automation features analysis
Workflow and project management
Smartling excels at traditional workflow automation. Its platform allows for the creation of sophisticated, rules-based workflows that can automatically route content to different translation stages, notify stakeholders, and manage deadlines. This is highly effective for organizations that need to codify and enforce a complex, multi-step localization process across a large number of projects.
Translated approaches automation from a different angle. While TranslationOS manages the end-to-end workflow, its most powerful automation feature is T-Rank™, an AI-powered system that selects the ideal translator for each specific job. Instead of relying solely on static project manager assignments, T-Rank™ analyzes a global network of translators based on their past performance, domain expertise, and real-time availability. This automates the critical decision of who is best equipped to deliver the highest quality translation, directly impacting the final output.
Quality assurance and review
Smartling employs automated quality assurance checks to identify potential issues such as glossary violations, formatting errors, or inconsistencies. These checks are a valuable step in a traditional QA process, helping to catch common errors before a human reviewer gets involved.
Translated integrates quality assurance directly into its AI feedback loop. The human review process is not just a quality gate; it is a core part of the AI’s continuous learning. As Lara learns from translator feedback, Time To Edit consistently decreases, meaning human effort is progressively refocused on higher-value tasks like stylistic refinement rather than basic error correction.
Integration ecosystem
A translation platform’s ability to connect with the enterprise technology stack is critical for achieving continuous localization. Here, the choice is between a vast library of connectors and a focus on deep, seamless integration.
Breadth vs. depth of integration
Smartling offers an impressive and extensive library of connectors for a wide range of CMSs, marketing automation platforms, code repositories, and help desk solutions. This “breadth” approach makes it an attractive option for companies with a diverse and complex tech stack, as it is likely to have an out-of-the-box solution for many of their systems.
Translated focuses on the “depth” and quality of its integrations. They offer a vast catalog, too, but they also provide a robust Translation API and develop deep, seamless connectors for the most critical enterprise systems. This includes major platforms like WordPress (via WPML), ensuring that the integration is not just a simple content exchange but a smooth, well-supported extension of the client’s workflow. This philosophy prioritizes the stability and performance of key connections, ensuring that the localization process is a reliable and integrated part of the enterprise architecture.
User interface evaluation
The user experience of a platform is a critical factor in its adoption and effectiveness. The ideal interface should empower both the managers overseeing the process and the linguists performing the core work.
The user experience for project managers
Both Translated and Smartling provide sophisticated, web-based dashboards that give project managers a centralized view of all localization activities. These interfaces are designed to handle complexity, offering tools for tracking progress, managing budgets, and generating reports. Both platforms successfully address the core needs of the localization manager, providing the visibility and control required to oversee a global content strategy.
The user experience for linguists
The experience of the professional translator is a key point. Within a standard TMS, linguists often work in a traditional Computer-Assisted Translation (CAT) tool, which presents segments of text for translation, correction, or post-editing.
Translated offers a different experience through MateCat. MateCat is a proprietary CAT tool designed specifically for professional linguists. It provides suggestions that are contextually aware and adapt in real-time.
Performance comparison
Translation quality and consistency
With a traditional TMS, quality and consistency are managed through tools like glossaries, style guides, and translation memories, enforced by multi-step human QA processes. These are effective but can be labor-intensive to maintain at scale.
Translated bakes quality and consistency into the core of its technology. Lara’s ability to consider full-document context ensures that translations are not just segment-accurate but holistically coherent. Because the AI learns from the choices of the best-performing human translators, it naturally propagates brand voice and terminology across all content. Consistency is not just a rule to be checked; it is an inherent characteristic of a continuously learning system.
Pricing analysis
While specific pricing details depend on the scope of an engagement, the pricing philosophies of Smartling and Translated reflect their underlying value propositions.
Understanding the value proposition
Smartling’s pricing is typically volume-based, aligning with its function as a platform for managing and processing translation tasks. This provides a predictable cost model for companies that need to budget for localization on a per-word or per-project basis. The value is transactional: you pay for a defined volume of work to be managed and translated through the platform.
Translated’s model is usually not just in the number of words translated, but in the creation of a proprietary, self-improving language asset. The return on investment is measured not only by the cost of the initial translation but also by the compounding efficiency gains and quality improvements that reduce long-term costs and accelerate time-to-market. The goal is that the platform becomes more valuable to the organization over time.
Customer success stories
The success of global brands often highlights the impact of their localization strategy. Companies like Asana and Airbnb have partnered with Translated to power their international expansion. These collaborations showcase the power of an AI-first approach, not just to translate content, but to enter new markets with the speed, quality, and cultural nuance required to build a global user base.