Hold onto your hats, content creators! The pace at which we bring ideas to life is changing rapidly, thanks to the swift advancement of AI-powered tools. Not only has AI become incredibly useful and efficient, but the development of advanced network...
Pangeanic, the Valencian leader in language technologies and natural language processing (NLP), has been officially recognized as an Innovative SME by Spain’s Ministry of Science and Innovation. This prestigious seal certifies the company’s high...
The TAUS Massively Multilingual AI Conference in Dublin on June 10-11, 2025 proved to be a pivotal moment for our industry, bringing together leaders from AI labs, globalization directors, and language technology providers at Google’s European...
Two recent signals from the world’s most influential players—the European Union and Google—have redefined how we think about LLM-based translation (or AI translation). Both the EU and Google now accept that AI-powered translation is fluent, usable,...
In the field of private Generative Artificial Intelligence (GenAI), a crucial component is transforming how virtual assistants access and utilize real-world knowledge: RAG, or Retrieval-Augmented Generation.
Pangeanic, a leading European language technology company, has...
Gartner's enterprise AI research confirms what we've been saying about the future of AI business models: multilingual agentic workflows are where the real opportunity lies.
In an era where AI can write code, translate languages, and even compose poetry, there remains one cognitive domain that is exclusively human: abstract thinking. Instead of fearing or mocking the generative errors or hallucinations produced by early...
Translating religious texts is among the most sensitive and complex tasks in the language services domain. These documents are not simply literary works—they are sacred, revered, and central to the spiritual lives of millions. They often contain...
| by Ana B. Fernández Bosch, COO |
In Artificial Intelligence systems, data quality is paramount. Poor training data—even in small proportions—can have devastating effects on a model’s final performance. Developers of all sizes understand...
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