Roboflow is a fantastic user-friendly platform that I have used extensively over the past year, mainly to annotate images that are subsequently used to train AI models. Roboflow allows one to annotated images from scratch. The annotated images can then be used in several ways.  First, they can be downloaded to a local computer and be combined with other (annotated) images in future projects.  This prevents the need to annotate a second time and one can choose to use the same train:valid:test distribution as was used in previous projects. Second, the annotated images can be used to develop a version of the project that can be used to train an AI model. Roboflow offers the possibility of preprocessing and augmenting the initial images to create a larger library of images that have a variety of rotation, brightness, hue, etc. Third, the annotated images can be used – via the project version – to train a model directly on the Roboflow platform. Alternatively, Roboflow supports the possibility to download the annotated images (including the preprocessed and augmented images) to another platform where the AI model can be trained.

What has provided the most value for me in Roboflow is the ability to collaborate efficiently during the annotation process, especially when working with academic teams. We often have multiple students and researchers labeling data simultaneously, and the shared workspace makes coordination seamless. Performance-wise, the platform is consistently fast, very intuitive, and reliable, even when handling large datasets or heavier annotation workloads. In terms of pricing, I genuinely feel that the credit system is very accessible. On several occasions, when I’ve run out of credits, I’ve been able to continue training models with as little as $5, which makes a huge difference for academic projects with limited budgets. The AI-assisted annotation tools have also been a major advantage. Features like automated labeling and the ability to integrate my own models significantly speed up the workflow. Using SAM 3 for annotations has made the process even more efficient, reducing manual effort and improving consistency across the team. An unexpected benefit has been how easy it is to onboard new contributors—students can start annotating effectively within minutes

i love how much possibility Robo flow brings. I love how simple it is to use as a first time user.