The best toolkit for advanced vision-language and generative AI development
Data redundancy can not only hurt model performance but also create significant costs for data labeling, storage, and compute.
Selecting the most valuable training data to achieve significant gains in accuracy. Leverage active- and self-supervised learning.
Manage your data and machine learning pipeline efficiently and leave hacky in-house solutions behind for a scalable solution.
Manage data curation runs and keep track of new data for labeling and model training
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"Through Lightly we were able to see, that a lot of data being collected was not meaningful enough for training an accurate model. This led us to change the way we gathered data and allowed us to ultimately create a much more information-dense and higher-quality dataset overall. Needless to say, the performance of our final model was greatly improved."
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“Lightly gave us transparency to a part of the ML development that is a black box, data. Furthermore, Lightly enabled us to do Active Learning at scale and helped us improve recall and F1-score of our object detector by 32% and 10% compared to our previous data selection method. We finally saw the light in our data using Lightly.”
“By integrating Lightly into our existing workflow, we achieved a 90% reduction in dataset size and doubled the efficiency of our deployment process. The tool’s seamless implementation significantly enhanced our data pipeline.”
“Lightly enabled us to improve our ML data pipeline in all regards: Selection, Efficiency, and Functionality. This allowed us to cut customer onboarding time by 50% while achieving better model performance.”
"Through this collaboration, SDSC and Lightly have combined their expertise to revolutionize the process of frame selection in surgical videos, making it more efficient and accurate than ever before to find the best subset of frames for labeling and model training."
"After training a model on the filtered data suggested by Lightly, I saw a dramatic increase in performance on our key metrics. Part of this is certainly because this was the first time we trained a model on any data that we've collected, but I'm fairly certain that performance would not have been as good if we had chosen what data to label at random."
"Lightly is hyper-focused on finding thousands of relevant images from millions of video frames to improve deep learning models. The Lightly platform enabled us to build models and deploy features more than 2x faster and unlock completely new development workflows."
Designed to seamlessly plug into your favorite storage, tooling, and service providers in order to build an automated data pipeline for machine learning that enables a closed loop feedback cycle.
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Learn how to get the most out of your data
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