DRIVE CONSISTENCY ON
QUALITY
The results are automatically and manually verified. We make sure you get only the high-quality labels.
CONFIGURE AND RUN
IMMEDIATELY
Configure for different use-cases and different data types. It takes 10 minutes to set up and run.
LABELING MADE
SCALABLE
Labeling big datasets can become tedious and expensive. Heartex can automatically label similar data samples.
Heartex is an annotation management system with configurable UI interface for your specific needs. Start using it and minimize the amount of time your entire team spends on preparing and analyzing datasets for machine learning.
Images
Use Heartex for analysing photos, CCTV footage, ecommerce, and other visual information.
Audios
Label audio files to filter out ads, transcribe speech, identify music genres and more.
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Texts
Parse human input, moderate messages, train chatbots for context recognition, build analytics over textual information
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Time series
Label time series and train different models to work with sensor signals
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Custom datasets
Set up models to work with any type of datasets you have — let us know of your objectives and we'll help you start either with our AI models or connect your own
We make suggestions based on what has already been processed before. You only need to approve or correct the suggestions while labeling your own datasets.
Heartex uses cluster annotation and active learning to train your model on diverse examples first. You can fine-tune the model by labeling similar objects later to optimize the model’s quality score.
If your data set has missing variables, or your collaborator labeling results differ too much, you'll see that early enough. Make adjustments and save time and money on labeling everything — just monitor the model's quality score at the early stages of training.
