AI for better human insights

Absolutely - and we can prove it.

Fairgen's pioneer data augmentation solution can generate near-real synthetic results into niche segments. As long as based on a model trained on your general audience survey.

Technical validation is a key part of every workflow in Fairgen.

Currently, any organization can apply online by scheduling an introductory call with our team. We are working on a Public Beta that will be open to our community. Be among the first to get access by joining our waitlist.

Insights teams can immediately expand coverage across niche markets, while gaining fast access do data and without the need of costly traditional data collection boosts.

Analysts can significantly reduce time-to-insights when it comes to niche markets, speeding insights delivery to its stakeholders and ultimately accelerating business outcomes.
‍
Access to once "impossible-to-reach" segments is an added value: by extrapolating results while maintaining high confidence levels, niche segments once considered too small, or too hard-to-reach for fieldwork boosts, can now be analyzed.

In short, you will run several parallel testing processes that will compare the efficiency of synthetic data versus real data.

The primary method used by our clients is "Backtesting", using as a base existing datasets. By the end of it, our predictive technology's accuracy and coherence both on aggregated and granular results can be determined.
‍
The process is simple: you will provide a fraction of an existing dataset for Fairgen to be trained on, so we can mimic a situation where you have scarce data. Let's say 10% of it. The remaining of it will be used as the ground truth and Fairgen will generate a synthetic dataset that was trained on only 10% of it. We will then compare its reliability against samples of the "ground truth".
‍
We guarantee a reliable and coherent augmentation that is worth 2x of any niche segment within your original dataset.

Yes. Fairgen is equipped to handle any quantitative (close-ended) data points that can be exported in a columnar format (single and multiple choice questions, rankings, NPS, continuous open-ended, ratings, and more). Fairgen automatically recognizes field types and conditional relationships between questions.