Image classification done right

Hasty’s online annotation tool is the first ever that uses a human-in-the-loop, AI-assisted annotation approach. The result? You can create classifications 10x quicker than ever before

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With our image classification AI tool, you will get quicker and more effective annotating.

Every annotation you make is sent to our model trainer that creates custom models based on this data. This custom-tailored approach to AI annotation means that you can get the assistance of our AI tool no matter what the use-case.

Human-in-the-loop approach

We don’t believe that annotation can be 100% automated. There will always be edge-cases that need human attention. We believe in humans and machines working together, playing to the strenghts of both. That’s why Hasty is the only labelling tool on the market with a human-in-the-loop approach.

Our models create classification suggestions. You accept the ones you like. You add what’s missing yourself. As you create more and more data, the suggestions will get better and better as we constantly retrain our models. Soon, you’ll find yourself classifying complex images quicker than ever before.

Automated labelling that labels 1000’s of images in minutes

With enough data, the need for a human dimnishes. You label 1000 images Our classifciation assistant is getting better and better. And you find yourself accepting all suggestions on image after image. Now it’s time to use our automated labelling feature. This enables you to batch-process all, or a portion, of the remaining images in one go.

Try Hasty for Free!

Jenny Abrahamson

Software Engineer
at Audere

“Before discovering Hasty, labeling images was labor intensive, time-consuming, less accurate, and progression through the groundwork to build our AI detection model was much more frustrating. Hasty’s approach of training the model while labeling with faster annotate-test cycles has saved Audere countless hours. The speed and ease of use have allowed us to accelerate our mission to improve global health in the world’s most underserved communities.”