Multi-origin Data Collection
Panel Data: Access our extensive, culturally rich panel database from DigaYGane.com, featuring millions of data points collected over a decade from Hispanic, Black, AANHPI, and LGBTQIA+ communities.
Synthetic Data: Generate synthetic responses using machine learning models trained on authentic multicultural datasets, ensuring culturally relevant and unbiased insights.
Enhanced Accuracy and Realism
Flexible Model Selection: Our approach applies a range of models, from statistical techniques to advanced machine learning methods, to create synthetic data that accurately reflects both single tables and complex, interconnected tables.
Comprehensive Quality Measures: Synthetic data is evaluated against real data across multiple dimensions, ensuring it upholds cultural diversity and accurately represents the target demographic groups.
Real-Time Generation: This methodology enables fast, on-demand data creation, allowing clients to access data whenever needed, even for highly specific or new questions.
Bias Mitigation
ThinkNow Synthetic is trained on multicultural data, prioritizing inclusivity, and minimizing biases. By incorporating a variety of communities and adjusting models accordingly, we ensure that generated data authentically reflects diverse populations.