Here’s how it works
First, we set up dataset and task guidelines to support API, .CSV, FTP, Cloud etc. Then our team of data labelling experts label your data to make sure your models are being trained on accurate and high-quality data. Further, our semi-automatic labelling process consisting of a combination of deep learning models, heuristics and manual human edits, creates high-quality annotation at scale. Finally, we execute multi-level labelling and manual quality checks over each and every data labelled, and machine checks to eliminate random or systematic errors to ensure highly accurate output.
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Pretrained & Customizable Models
A machine learning model is only as good as its data labelling models. Fullestop is an end-to-end solution provider that works to create accurate training data, manage the data, and process it all in one place. We provide customizable models that support production pipeline with powerful APIs based on individual requirements.
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Reduced Labeling Costs without Sacrificing Accuracy
Machine learning assisted data labelling can be very expensive. To solve this problem Fullestop has combined machine learning with our expert human annotators that train your data with utmost accuracy, saving you time and money without sacrificing accuracy.
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Automatic Routing and Labeling
Automatically routing and labelling the most important data with API driven labelling queue prioritization. Fullestop uses this technique to significantly improve labelling productivity. Combine model-predicted labels for the data labelling process along with Fullestop's Automatic Routing and Labeling to see the greatest improvements and the most seamless process.
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Enterprise Scale with Total Control
Machine learning-powered workflows allow for most of the data to be labelled by a machine, with high accuracy thresholds. For the remaining data, you can use labellers as per your requirement. You can leverage from our highly-trained human data labellers or you can use your own internal resources for sensitive projects.