Hundreds of companies and researchers use Supervisely every day to label images, videos, LiDAR 3D sensor fusion or even DICOM volumes, manage datasets, collaborate together and train neural networks. But that's just part of the story.
Unlike other products, we create the true platform that integrates countless open-source tools and custom built solutions within a single ecosystem using Supervisely Apps — interactive web-apps running in your browser, yet powered by Python.
Just like a real OS, Supervisely gives you unlimited customization and variability, aiming to solve every task in computer vision.
There are hundreds of features within the platform, but everything we do is defined by these five concepts.
Best-in-class tools, augmented with AI-assistance and custom UIs
Secure your data and joint efforts with all-in-one platform
The best models, ML tools for analysis and model improvement
Ready to use apps or custom extensions with Python & VueJs
Self-hosted edition for companies that value their privacy
Pixel-accurate annotations with advanced ML-powered tools for every case.
Packed with advanced annotation tools, Supervisely provides a comprehensive set of features that distinguishes it from other labeling tools.Explore image labeling
Label hours-long videos without cutting them into images. In your browser, with a multi-track timeline, built-in object tracking and segments tagging.Explore video labeling
Label comprehensive 3D scenes from LiDAR or RADAR sensors with additional photo context, AI tracking and point cloud segmentation.Explore 3D labeling
Label volumetric medical scans from CT and MRI in 2D or 3D with professional viewer, advanced editing tools and AI enhancements.Explore DICOM labeling
Apart from usual tools like rectangle or brush, Supervisely comes with “smart” labeling tools based on a collection of class-agnostic neural networks that can be further trained on your data.Learn more
Neural network in the core of the smart tool can be re-trained to better fit your very unique case and produce unprecedented results with just a little bit of extra data.
Smart tool is class-agnostic — it was not trained to capture specific objects, but rather any forms that stand out.
Management and collaboration tools that help you sort your valuable assets out and perform quality and performance monitoring and automate routine operations.
Focus on labeling and let Supervisely do the rest.
Don’t miss relevant information and stay informed of what’s going on.
Get notifications in your Supervisely dashboard, an email or web-hook event when you are assigned a new labeling job for annotation or review or when you receive a new feedback in issue tracking.
Get yourself a peace of mind with built-in backup system and two-level trash bin.
Each user has a trash bin they can empty, but only an instance administrator can confirm final data removal from the server.
A built-in issue tracking includes comments, available right inside the labeling interface. Chat on what needs improvement to deliver quality results faster.
Total commander inspired data manager lets you view, rename and copy anything, from teams to datasets.
Invite or manually organize your users into private teams with custom access roles which control access to different features and resources.
Let your manager download project, but deny labeler to remove existing annotations.
Not every annotator properly understands labeling requirements from the day one and often makes systematic errors.
Ensure your annotation policy is well presented and acknowledged with annotation guides that include rich text content via markdown, videos and pdf documents, available for the specific team or everyone.
Supervisely is probably the only machine learning platform that not only provides easy and convenient access to the state-of-the-art models and machine learning tools right in your browsers, but inter-connects hundreds of previously isolated projects on a single platform as Supervisely Apps.
We aim to cover every single use case and aspect of the machine learning pipeline, not just a few most common ones, by building a true platform that works like OS for computer vision.
Configure every aspect of training from target classes to online augmentations, monitor metrics and terminal logs in real-time.
Understand how your model works on ground truth and new data and find how to correct negative output and increase performance.
Put pre-trained or custom neural network models to use in labeling interfaces to archive extraordinary results.
Generate synthetic datasets that drastically improve model results, especially when there is not enough ground truth.
We have some of the best AI architectures and models integrated on the platform as Supervisely Apps. That means, every model:
Moreover, as soon as model is deployed, you can use it other applications and labeling tools.More about models
Build models from labeled data using the best architectures
Deploy trained models as API on cluster and use in other Apps
Use served models in infinite various applications
Universal format and unified application engine made it possible to create an ecosystem of hundreds machine learning tools you immediately get access to.
Waste no time on dataset format converting
Make more data from existing content
Create enormous datasets from different sources
Save results in any format you need
Waste no time on dataset format converting
Skip the most challenging part of machine learning — data labeling! Programmatically compose datasets from different assets and generate infinite amount of synthetic data samples.
Dramatically improve training results by mixing them with real-world examples: all automated with Supervisely!More about synthetic data
Apart from other companies that run monolithic black boxes with little to no customization and community involvement, we build a true platform that provides a foundation for everyone to develop and run applications — just like in OS, like Windows or MacOS.What makes us different?
Constantly growing ecosystem of hundreds of ready-to-use apps that extend and add new functionality.Explore Supervisely Apps
Built as OS for computer vision, Supervisely runs on Apps that're easily created or tailored to fit your needs. Custom labeling UIs, integrated neural networks or import and export in your internal format are just some examples of what can be done by our or your developers.
New functionality is added via Supervisely Apps — self-contained GUI extensions (server + frontend) that integrate existing solutions from GitHub (like neural networks) or extend the platform with task-tailored features, like custom labeling UIs. Apps can co-operate with other Apps, thus, a new App makes every other App on the platform more useful.
With Supervisely you don't have to choose between a general, well-tested set of tools to solve a common task like labeling and a custom tailored solution that you, and no one else has. Our team is not only committed to getting the job done, but also has the right tools for that.
Usually, it's just as it is. The best case scenario, existing functionality covers your today needs, but think, what happen, if new challenges will arise in front of you, outside of the software scope? Will they adapt it for you? Can you contribute in development?
Generally you get the software in its final form. Every new feature should go though the whole discussion, development and provisioning pipeline before you can get your hands on it, if that's an option at all. If you are very lucky, maybe, there are some kind of plugins, limited in possible functions by the software API — you won't build a custom video tagging toolbox on it.
A hard-coded product can offer you a great solution for 90% of your tasks. But what happen with the other 10%? Often, you need to hire an extra workforce to develop the missing link and deal with two, three or even more pieces of software, trying to make them work together.
Supervisely Enterprise Edition (EE) is built for companies that want to scale their AI infrastructure, available in both cloud and self-hosted installation. More user governance and security features. No limitations!Enterprise Edition
Hosted behind a firewall on your servers, Supervisely works without any access to the outside world.
Ready for datasets of Terabytes sizes and hundreds of users working simultaneously.
Make sure only approved people have access to your data in Supervisely by setting up team roles and SSO.
Deploys well in both on-premise container systems like Kubernetes and cloud like AWS EKS.
Supervisely can be installed and updated by using an included supervisely-cli command.
Use LDAP, Microsoft Active Directory and Oauth2 SSO providers for improved security.
Work with existing data on AWS S3, Google Cloud or Azure — no need to re-upload data again.
We use best tools and conventions, like encryption, system logging and data uploading verification.
We create a dedicated Slack workspace with an account manager that assists throughout the onboarding, installation and during the whole 30-days or more free trial. Schedule personalized training sessions with our experts and get Supervisely tailored specially for your use case.
We have the top specialists to understand your use case and suggest the best solution.
Try us in action with our expert guide — and if you will need more time, we will extend it.
If you will find that some features are missing it’s not a problem — we will help to customize it with Apps.
We use Supervisely since 2019. The key advantage of this tool is that Supervisely provides a complete data treatment pipeline. An important advantage is that a Supervisely instance can be deployed autonomously on a Client infrastructure, and distributed on different servers.
It helps to treat enterprise’s internal and often confidential data in a secured way. Together with a user-friendly interface, a clear documentation and a friendly and reactive support team it helps us to do Data Scientist work better and faster.
BMW Group is using the Supervise.ly solution to create automated verifications for ensuring a very high product quality across the whole production chain in vehicle and vehicle component manufacturing.
BMW Group uses Supervise.ly to annotate manufacturing images from production lines in their world-wide plants for enhancing quality inspections using deep learning. The Supervise.ly tooling also supports the process for continuously updating AI models using semi-automated labeling.
Supervise.ly is integrated into the BMW Group AI Platform in order to empower computer vision based AI use cases.
We originally set out to look for tools that could help us with data annotation, and we discovered that Supervisely excels at that and much more. It has become an integral part of our workflow in annotation, model training, and evaluation.
We've been exceedingly impressed with the customer support, addition of new features, and the flexibility of the publicly available SDK/API. The Supervisely team has also been fast to respond to support questions, and has shown a lot of openness when given feedback on potential improvements.
We have been using Supervisely for a few years now to help label and organize our data for AI training. The interface is user-friendly and the tools are intuitive to use, which has made the annotation process much more efficient for our team. We run Supervisely locally, which allows us to stay in control of our data. We also use Supervisely for annotation reviews, and the review tools have been invaluable in ensuring the quality and accuracy. The Python SDK has also been incredibly helpful in automating and streamlining our workflow. In addition, the support team on Slack has been extremely helpful and responsive. The ability to collaborate with my colleagues on the same project has also been a huge time-saver.
Overall, we have been extremely satisfied with Supervisely and would highly recommend it to anyone in need of a reliable and efficient annotation solution.
Supervisely provides first-rate experience since 2017, longer than most of computer vision platforms over there.
Join community of thousands computer vision enthusiasts and companies of every size that use Supervisely every day.
Our online version has over a 220 million of images and over a billion of labels created by our great community.
Speak with people who are on the same page with you. An actual data scientist will:
Get accurate training data on scale with expert annotators, ML-assisted tools, dedicated project manager and the leading labeling platform.Order workforce