Data labelling represents 65% of the time for a NLP project, and engineers don't like to do it. Improve the speed and accuracy of your data labelling with:
Generic labelling leads to generic models. Customize your labelling set up to create the data you need to elevate your models.
Unlock AI’s full business impact with a tool built specifically for NLP labeling, ready to be customized for your team’s requirements. All while retaining ease of use.
Errors are inevitable in data labelling, but that doesn't mean they are easily found. Quality data leads to equality models, catch the issues at source.
Take advantage of QA capabilities that allow for high-level and granular reviews of labels and labelers to ensure data quality. Accelerate ideation to output, with 10X improved project times.
Data labelling is manual work, but it doesn't have to be. Automate tasks that are oft-repeated.
Increase your team’s time by automating monotonous labeling tasks. Let them focus on building better models instead. Automate the bulk of the labeling workflow, from project setup and export to labeling itself.
Get a feel for how easy labeling can be with this example of NER token-based labeling in the Datasaur Playground.
We [Consensus] had a very complex and specific set of annotation needs. Datasaur was able to address those needs efficiently and effectively.
Information labeling tasks has been reduced by 80% which has allowed us to optimize our workflow much more, allowing us to focus on other areas that are also priorities for us.
"We looked at Prodigy, LightTag, LabelBox, Scale and more. You really can't beat Datasaur for their suite of features and price point."
