Rabot and Lightly have worked together closely to tackle the above challenges.
Lightly selects the most relevant data to help Rabot retrain its model for each customer as part of its machine learning pipeline. It uses the self-supervised learning feature to find the most diverse images.
Thanks to Lightly, Rabot reduced the amount of data required for retraining, resulting in a higher speed for retraining. In practice, Rabot could identify the 10% relevant training data while keeping model performance high. Thus, shortening the retraining process time by 50% significantly resulted in a 2x faster customer onboarding for Rabot.