AI-powered consensus scoring

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.

Instance Segmentation

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.
Object Detection

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.
Label Classification

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.

"Before discovering Hasty, labeling images was labor intensive, time-consuming, and less accurate. Hasty’s approach of training the model while labeling with faster annotate-test cycles has saved Audere countless hours."

Jenny Abrahamson
Software Engineer at Audere
"Hasty.ai 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."

Dr. Alexander Roth
Head of Engineering at Bayer Crop Sciences
"Modern tools like Hasty are very accessible for everyone at Element Six to harness the power of AI with a relatively low investment"

Tanmay Rajpathak
Applications engineer at Element Six
"We needed a partner who could help us improve our labeling efficiency and keep our quality standards high. Accelerated Annotation offers a compelling platform backed by a reliable workforce. We saw 75% efficiency gains and preserved quality, giving us exactly what we were looking for in a partner."

Julian Seidenberg
Head of Artificial Intelligence
"Because of Hasty, PathSpot has been able to accelerate development of key features. Open communication and clear dialog with the team has allowed our engineers to focus. The rapid iteration and strong feedback loop mirrors our culture of a fast-moving technology company."

Alex Barteau
Senior Computer Engineer at PathSpot Technologies
"Hasty has taken our data labeling to the edge. Both semantic and bounding box labeling has gone from weeks or months on our large data sets to days. For QA, I just reviewed 19,000 labels in 5 hours. WTF!"

Shane Prukop
CEO at TruPart Manufacturing

Revolutionizing QA with our AI consensus scoring

Why look for errors when you can fix them?

Better data for a fraction of the cost

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

Getting the full picture

"Before discovering Hasty, labeling images was labor intensive, time-consuming, and less accurate. Hasty’s approach of training the model while labeling with faster annotate-test cycles has saved Audere countless hours."

"Hasty.ai 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."

"Modern tools like Hasty are very accessible for everyone at Element Six to harness the power of AI with a relatively low investment"

"We needed a partner who could help us improve our labeling efficiency and keep our quality standards high. Accelerated Annotation offers a compelling platform backed by a reliable workforce. We saw 75% efficiency gains and preserved quality, giving us exactly what we were looking for in a partner."

"Because of Hasty, PathSpot has been able to accelerate development of key features. Open communication and clear dialog with the team has allowed our engineers to focus. The rapid iteration and strong feedback loop mirrors our culture of a fast-moving technology company."

"Hasty has taken our data labeling to the edge. Both semantic and bounding box labeling has gone from weeks or months on our large data sets to days. For QA, I just reviewed 19,000 labels in 5 hours. WTF!"

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