Annotation services

Boost your ML efforts with our
in-house labelers

Ensure the highest quality training datasets, from fashion
and automotive to medical and agriculture cases.

Why choose LinkedAI?

Faster, better and with the ability of scaling to meet your company’s very own needs! LinkedAI is the best option to accelerate your labeling process and obtain the highest quality training datasets reducing time and costs.  Best part? We offer a no-obligation free trial, no hassle and no commitment!

On-demand
dedicated team

Our in-house highly-trained data labelers are able to deal with any data challenge. As your data labeling needs grow over time, you can count on us to scale the workforce needed to meet your goals.

Best in class
Quality

Our ML-powered process and our highly-trained team are the perfect duo to achieve accuracy over 99%. We will provide you high-quality training data at a fraction of the cost, in less time.

ML Powered
Process

Our ML models pre-label the data to remarkably reduce the cost and time required to label your data.

Synthetic data
generation

We provide synthetically generated images to enhance your dataset and achieve higher object detection accuracy.

Which image annotation type is right for your project?

Our platform has all types of labels. You can choose the one that best suits your use case.

How do we work?

Recommended by leading
innovation experts

“With LinkedAI we sped up the labeling process, reducing in half the time needed to analyze data. This ended up largely improving our object detection and segmentation backbone.”

David Cardozo from Kiwibot - AI & Robotics Lead

Success stories

This motor insurance company needed to automate the process of assessing the condition of vehicles, in order to improve the effectiveness and speed in calculating car damage. Discover how they used our labeling tool to annotate and deploy a product that process claims faster and with less administrative costs.

Find out how this company leveraged LinkedAI to reduce by 97% operating costs and started counting and analyzing tomato plants at super human speed in less than four months.

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