In the early stages of model development, experimentation is the most important activity.
Data science teams need control and flexibility to rapidly configure and experiment with new labeling requirements and metrics. Even after they’ve proved a model, many data science teams still want a completely customizable annotation environment that they can use as needed for further experimentation or for privacy and security reasons.
After all, how can you properly set up your data labeling requirements when you’re not even sure what you need? Or how do you understand what you need to do before you can commit to scaling an ML or AI initiative? There should be a way for data science teams to quickly log in and use a tool that gives them more information about where their model stands.
This is what we set out to solve with the launch of Alegion Control, our new self-service video annotation option. With Alegion Control, data science teams are now able to get full
access to our powerful annotation platform with the ability to customize and test their training data and models without the commitment of time and money that comes with a typical enterprise solution.
