Nitrode begins with internal benchmark tests aligned to a client’s spatial reasoning goals and target use cases. We evaluate model performance across spatial relationships, object interactions, movement, and state transitions to identify specific failure modes. Data is then created or sourced only where benchmarks reveal clear gaps, ensuring each dataset directly improves real-world performance.