Mission
Mission
Founding Purpose, Core Values
We share our vision for a future where AI is inclusive, responsible, and empowers communities and businesses alike. Join us in shaping technology that reflects the diversity of the world.
Our mission
Our mission is to advance AI systems that robustly understand and serve every language, not only those most represented in today’s frontier benchmarks.
We are an AI research company focused on a critical but under-addressed problem in modern machine intelligence: current frontier models show consistent and measurable performance gaps across languages, with underrepresented languages systematically underperforming in comprehension, reasoning, and generation tasks.
This is not simply a data imbalance, but a deeper research limitation in how multilingual generalization is modeled, evaluated, and optimized in today’s large-scale training and benchmarking paradigms. As a result, progress in language AI has not translated evenly across the world’s linguistic diversity.
We exist to close this gap through research that improves cross-lingual generalization, evaluation methodologies, and model robustness across diverse linguistic structures ensuring that advances in AI translate into equitable capability across all languages.
Our principles
Guiding principles for AI research
Safety First
Prioritize the development of AI systems that are safe, reliable, and aligned with human values before optimizing for capability or speed to deployment.
Responsible Transparency
Be open about research methods, findings, and limitations while carefully managing dual-use risks that could enable harm.
Long-Term Thinking
Make decisions with multi-decade consequences in mind, not short-term incentives. The impact of foundational AI research compounds over time.
Rigorous Empiricism
Ground all claims in evidence. Maintain scientific humility and value negative results as much as positive results.
Human-Centered Design
Build systems that augment human capability, preserve agency, and enhance dignity rather than replace human judgment.
Inclusive Benefit
Ensure AI capabilities and their benefits are distributed broadly rather than concentrated among a small set of actors or regions.
Collaborative Ecosystem
Engage with academia, policymakers, civil society, and other research labs. The challenges of AI require collective progress.
Ethical Accountability
Maintain governance structures with authority to pause or redirect research when risks exceed acceptable thresholds.
Human Oversight
Strengthen human ability to understand, monitor, and govern AI systems throughout their lifecycle.
Intellectual Integrity
Foster a culture where researchers can challenge assumptions freely and where truth is prioritized over prior commitments.