Helping humans teach machines to see the world
Next Generation Image Annotation – higher levels of automation, iterative workflows, and exponential speed achieved by training the model while labeling.
Label your data in a fraction of the time
Automate over 70% of the work needed to train an AI model. Experience much faster labeling, be more confident in your data, and deliver successful projects, without the heavy lifting or up-front resources you needed before.
Be Fast
See first results in hours, not months. Getting actionable feedback from Hasty’s AI assistants is like having an extended annotation team 24/7, helping you speed up the process of data labeling and improve data accuracy. The more you use Hasty, the faster and better it gets.
Be Agile
Get instant feedback on what's working and where there's room for improvement. Hasty’s Rapid Feedback Loop™ lets you see what the models understand and where they struggle, enabling you to iterate quickly and adapt your approach as you go.
Be Accurate
Find and correct errors in your ground truth data with Hasty’s manual and AI-powered Error Finder features. Hasty's Error Finder takes you to the most likely issues in your training data, eliminating the hours needed to color match annotations or search for artifacts.
Be Part of a Community
A tool is only as good as its users. Hasty is built by and for machine learning engineers and data scientists. As a community, we learn from each other, ask questions and get answers from other ML engineers. Contribute with your experiences to help make more CV projects successful. Join our community.
Try Hasty for Free!
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.”