All annotation is now free in Hasty.

Revolutionizing QA with our AI consensus scoring

With Hasty, you can use AI to find potential errors and outliers for you and concentrate on fixing issues, not finding them. This makes the process of QA 35x cheaper than before.

Why look for errors when you can fix them?

Today, almost all quality control and assurance is done completely manually. Whole teams sit and go through image by image to find potential issues, spending up to 30% of their effective time on this one task.

With our new AI Consensus Scoring, you can use AI to find potential issues for you, and then accept and reject our suggestions. This approach has been shown to give you the same data quality 35x cheaper.

Better data for a fraction of the cost

By fixing instead of looking for errors, you can get incredible savings when doing QA without seeing any difference in quality of your data. After all, you are the one deciding what is an error and what isn’t - we only give you suggestions on what to fix.

State-of-the-art AI to find issues for any problem

With our AI Consensus Scoring, you can find problems no matter what type of data you have. We can help you with finding wrongly classified bounding boxes, badly positioned polygons, and even artefact masks left from an erronous click.

Getting the full picture

We also give you a report on how many errrors we found, and if there are any particular patterns for what we see as potential issues. That approach gives you the full picture of how your previous annotation sprint went allowing you to quickly inform your team on where more attention is needed.

Tuple helped us improve our ML workflow by 40%, which is fantastic. It reduced our overall investment by 90% to get high-quality annotations and an initial model.

Removing the risk from vision AI.

Only 13% of vision AI projects make it to production, with Hasty we boost that number to 100%.