Roboflow
A computer vision workspace for preparing datasets, labeling images, training models, and deploying hosted or edge inference.
About Roboflow
Roboflow covers the working parts of a computer vision project in one place: dataset preparation, labeling, model training, and deployment. It accepts common image and video formats, exchanges annotations through JSON, XML, CSV, and TXT, and includes preprocessing and augmentation tools. Trained models can assist with later labeling, which reduces repetitive annotation work. Once a model is ready, teams can use hosted inference or deploy at the edge, depending on latency and connectivity needs. The free Public plan suits learning, prototypes, and open projects, but its data and models are visible to every user. Growth and Enterprise add private workspaces plus higher or custom limits. Roboflow fits developers who prefer a managed path from raw media to inference. Teams with strict access controls, larger datasets, or heavier usage will need to budget for paid capacity and possible enterprise add-ons.
Best for
Best use cases
Turn a collection of images or video into a labeled, augmented dataset ready for model training.
Train a model, use it to assist later labeling, then serve inference through hosted infrastructure.
Move inference to an edge environment when local processing, connectivity, or response time shapes deployment.
Compare before choosing
Choose Roboflow over separate point tools when workflow continuity matters more than assembling each stage yourself.
The free Public plan is attractive for open projects, while private data requires a paid Growth or Enterprise workspace.
Enterprise is the better tier when role controls, SSO, scoped API keys, or custom capacity affect procurement.
Features
Manage vision datasets
Upload images or video, label data, search datasets, inspect analytics, and prepare versioned training data in one workspace.
Train computer vision models
Train vision models from prepared datasets and use trained models to speed up later annotation with model-assisted labeling.
Deploy model inference
Run hosted inference or move models to edge environments when latency, connectivity, or local processing requirements call for it.
Pros
- One workspace connects dataset preparation, labeling, model training, hosted inference, and edge deployment.
- The free Public plan supports substantial open projects with up to 250,000 workspace images.
- Support for common media and annotation formats reduces conversion work when importing or exporting datasets.
Cons
- Public-plan data and models are open to all users, so private projects require a paid workspace.
- Growth includes only three team members and twenty projects, which may create added cost as collaboration expands.
- Advanced controls such as SSO and scoped API keys are Enterprise add-ons rather than standard free features.
Pricing Plans
Public
- Open data and models
- Up to 250,000 workspace images
- Up to 3x image augmentation
- 2 team members
- 10 projects
Growth
- Private workspace data and models
- Uncapped dataset size with pay-as-you-go usage
- Up to 5x image augmentation
- 3 team members
- 20 projects
Enterprise
- Private workspace data and models
- Custom credits and team size
- Custom augmentation limits
- Role-based access control
- Optional SSO and scoped API keys
* Pricing information is for reference only. Please refer to the latest announcement on Roboflow's official website.