Prompsit Language Engineering is a Spain-based language technology company that creates high-quality multilingual datasets and evaluation resources for machine translation, localization, LLMs, and domain-specific AI systems.

We specialize in the full data lifecycle: web corpus discovery, multilingual crawling, text cleaning, language identification, parallel sentence alignment, domain filtering, terminology handling, dataset quality assessment, and machine translation evaluation. Our team works at the intersection of language technology, data engineering, and practical localization workflows.

We contribute to Mozilla Data Collective because we believe that trustworthy AI requires trustworthy language data. The datasets we share are designed to be more than raw collections of text: they are curated, documented, quality-scored, and packaged for concrete use cases such as MT training, LLM evaluation, multilingual RAG, localization robustness testing, and low-resource language technology.

Our goal is to help researchers, AI companies, public-interest organizations, and localization teams access language data that is useful, transparent, and responsibly prepared. We pay particular attention to provenance, licensing, data quality, metadata, intended use, and known limitations.

Prompsit’s main areas of expertise include multilingual corpus creation, bilingual data alignment, dataset cleaning, domain-specific data selection, MT and LLM evaluation, terminology-aware translation workflows, and privacy-conscious data preparation.