Our Analysts' Insights

The question – since the earliest days of the computerized language industry – has been whether translation companies are so different than other service business that they can’t use generalized software. The argument was that generalized applications, such as FileMaker or Microsoft Word, with vastly more engineers, features, and user communities, would prove more useful in the end than would industry-specific applications and business platforms with small R&D teams and limited feature sets. ...

From their earliest stages, LSPs face the question of whether to build or buy the software on which they run their business. Triggers can include the need for differentiation, the need to tailor work processes for different customers and job types, or the requirement to stitch together disparate systems for monitoring and reporting. The question of when to begin proprietary development is important because if they wait too long, they may miss growth opportunities. But jumping too soon can result...

New technology developments are stirring up the language industry, but the buzz mostly centers around neural machine translation (NMT) and artificial intelligence (AI). Something else is afoot that most observers are not discussing: the shift from monolithic to distributed systems. Microservices addressed via REST APIs promise to increase agility by allowing swappable engines. During a recent CSA Research Colloquium at LocWorld, we put this new solution architecture in the context of enterprise ...

Technology is crucial for language service providers (LSPs), not just for growth but even for survival in a rapidly changing market landscape. Earlier this year, we reviewed technology survey answers for 728 providers and interviewed a cross-section of 30 translation and interpreting companies in 12 countries. Using this combination of quantitative and qualitative data, CSA Research wanted to see how aligning the LSP Metrix™ maturity model and the Tech-Savvy typology – originally published in ...