Collaborative Data Labeling
for Internal Projects

Accurate, scalable data labeling starts with Heartex.

Your business requires accurate, dependable models.

The question is, can you deliver?

Building machine learning models that consistently deliver accurate predictions to the business is easier said than done. Data Science teams have to manage a complex series of steps to acquire & prepare source data, engineer features, label data, train & test models, and deploy to production.

Don’t despair, with the right strategic investments and a little ingenuity, you’ll be delivering accurate predictions in no time. Just remember, Rome wasn’t built in a day and the best models aren’t either.

Accurate models start with high-quality data labeling.

To get accurate predictive value out of your models, you have to put quality labeled data into your training. What does it take to generate accurately labeled data at scale?

Us

Process & Tools

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A process rooted in quality and powerful, easy to use tools deliver predictably good results.

Data Type Variety

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Data is everywhere, label it all. Label images, text, videos, and more.

Quality Management

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Mistakes happen. Find them and fix them before you predict.

Results

Labeled Data

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Download and use labeled data to train your models or use it for analytics.

Accurate Predictions

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With full control over the labeling process you get higher quality models ready for production.

You

Raw Data

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Models trained with more data perform better.

Subject Matter Expertise

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To label accurately you have to know what you’re labeling and why.

Get accurate data labeling at scale.

Your model and your business will thank you.

Heartex’s centralized platform streamlines the labeling process, maximizing throughput while also improving label quality. Whether you label data internally, through a third-party service, or use a hybrid approach, Heartex Label Studio delivers: