After conducting an extensive research of annotation tools, we chose V7 as it fits our needs best due to its customizable workflows and automated QA.Read case study ->
We use V7 to make our annotation and model training workflows more efficient. It's much easier to use than other software thanks to its intuitive UI.Read case study ->
We did a comparison when we started and noticed an increase in efficiency when we changed the workflow. Thanks to V7, we no longer have to waste time.Read case study ->
Automate labeling and maintain control over your annotation process. Scale up your training data creation 10x times and deploy reliable AI solutions.
Pick a model type, train, and run your models in the cloud on V7’s scale-agnostic engine or your own instance. Switch on a webcam, and view the results right from your browser.
V7 allows you to create secure and reliable AI solutions, compare model performance, and connect them into automated workflows.
The security of your data is our top priority. We are SOC2 compliant and enable SSO integration so that you can rest assured that your data remains protected and private.
Spot label quality issues early and send data to annotation teams for re-work. Build robust review and consensus workflows to ensure quality and shorten the time to production. Improve your ML model performance by improving your datasets.
Turn your labeled data into models and run models directly from V7 in a matter of minutes. Use our pre-trained architecture to enable your model to learn with very few training samples. Leverage V7’s iterative model training capabilities and ship performant AI faster.
Use Pytorch Dataloaders to create datasets to train your own models on V7. Solve classification, object detection, instance segmentation tasks, and more.
Get immediate results from inference API. You can also switch on the webcam and test the model directly from your browser.
Register your own model via REST API, add it to your custom workflow and run it to label your training data 10x faster. You can register any model that is exposed via HTTP and manage it the same way you do the ones trained using V7.
Luckily, solutions like V7 came up, which are maturing in the industry, helping companies like ours to scale up and stay ahead with our R&D
Use models to label objects at scale, automate ML Ops, or compare their performance against humans or other models.
Keep all your company models in one place. Deploy them for model-assisted labeling tasks or use them to train new AutoML models.
Handle any vision output with equal performance, from simple classification to object detection to keypoint skeleton fitting.
Capture data in production and send it to a dataset for annotation. Add more knowledge to models for their next training session.
Run models in the cloud on the scale-agnostic Wind engine, switch on a webcam, and view the results right from your browser.
Combine models, humans, and data in composable workflows.
Run your models through sets of images and compare versions
Keep your production AI in top shape by ensuring each new version passes strict IoU tests
Ensure you’re always using the most accurate version available
Each model you import or train surfaces their accuracy across multiple metrics
Present your model results to your team in beautiful interactive graphs
Monitor metrics like accuracy, precision, recall, and F1-score across your team’s models
Solve any labeling task 10x faster, train accurate AI models, manage data, and hire pro labelers that care about your computer vision projects