Companies with a tech-based data classification solution located in the US or Israel. Participants should have a working product with existing customers (whether paying or pilot).

Companies which meet the eligibility requirements and have the highest coverage as well as accuracy and precision rate will be given a priority. 

Two weeks before the challenge, participants will be provided with a rich dataset of golden annotations for training with 20K+ synthetic records. The goal is to recognize 20+ types of entities in unstructured data. Each record may include a single annotation, multiple annotations or none. In the detection phase, given an input string, the analyzer/trained model should return a list of detected entities. 

On the day of the challenge, each participant will be provided with an unannotated dataset of 20K+ records at a scheduled time. A JSON file with the associated predictions should be submitted within 20 minutes. Upon submission, participants should also provide any 3rd party service used in completing the challenge.

The responses will be measured according to the following methodology: the performance for each entity type will be evaluated separately, in addition to a global, cross-label evaluation. Our evaluation metrics take into account partial matches, meaning an overlap (but not an exact match) between a detected entity and a same-type true entity. For each detected entity, we then measure precision and recall. Finally, we evaluate the overall performance by a weighted calculation of the grouped labels, taking into account their necessity and frequency. Each submission will be given a score according to that methodology. The winner will be the company with the highest score.

The winner will receive a $10,000 prize and will be invited to meet with Intuit senior executives.