Research
Data quality makes
all the difference.
We're driven by the conviction that model performance is fundamentally bounded by training data quality. Through expert collaboration, rigorous curation methodologies, and deep domain expertise, we research datasets that power tomorrow's models.
Core Research Areas
†AI Safety and Security
Our research focuses on developing novel approaches to AI training that help models understand and respect human values without sacrificing capability.
÷Multimodal Learning
We advance AI's ability to understand and reason across visual, audio, and textual modalities simultaneously.
>Computer Use & Automation
We've created training data that teaches AI agents to understand context, anticipate user needs, and execute complex multi-step workflows across diverse software environments.
∈Data Quality & Curation
We've developed rigorous methodologies for identifying, filtering, and enhancing training data quality to drive superior model performance.
∑Model Evaluation
Our evaluation frameworks go beyond traditional benchmarks to rigorously assess real-world AI performance across diverse real-world scenarios.