A single application for all your vision AI needs
Everything you need to go from raw images or videos to production-ready model in one tool. No MLops skills or tricky integrations needed.
Hasty was founded in Berlin in 2018 by engineers who wanted to make it easier, faster, and cheaper to get vision AI into production environments. Having worked on a broad range of AI projects for the German manufacturer space, we found ourselves spending countless hours doing manual annotation and ML Ops for what seemed simple use-cases.
Today, we take care of all the distractions and roadblocks for you so that you can focus on what matters - putting vision AI into production.
Create, compare, and deploy vision AI models
With Model Playground, you can create your models, tuned to the smallest parameter, and then deploy those models back to our annotation environment for unparalleled annotation speed - or export them and deploy them in your environment.
Using AI to train AI
The idea behind Hasty's annotation solution is simple. You annotate images, and we use the annotations to train AI models that make it faster to create more annotations. This continuously improving approach ensures that you build your data asset up to 12x faster than ever before.
Keeping you in control and keeping your data safe
The vision AI-space is full of tools that tell you they have the solution to your problems. Most of them come with an asterisk next to them.
With Hasty, you’re in complete control of your data. It’s never shared or used to train models that benefit anyone else than yourself (It’s even in our T&Cs).
Getting started is easy
Sign up and try for free or book a demo with one of our experts
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.”