Plot the best routes for your training data. Ensure the quality and cut down on AI model delivery times through automation
V7 offers you eight workflow stages you can arrange, connect, and loop in any way you need
Thanks to V7, we no longer have to waste time transferring files because everything is in the cloud - you just click it, and it loads - it helped us save a lot of time in admin.
The easiest low-code experience to help you train and ship performant AI
Gain insights into your data at every stage of its journey. Spot bottlenecks and resolve them without communication overhead.
Create your own workflow or pick one from our library of workflows templates. From simple to complex data projects - V7 allows you to customize your data pipelines to solve any computer vision task, at scale.
Easily build and automate a workflow process to take your data from its rawest form to being enriched with annotations. Set up your workflow once and use it for multiple data projects.
Drag and drop stages to connect them into custom workflows. Leverage no-code interface and complete your AI projects without dev help.
Turn your labeled data into models and use them to label more data. Run and improve models iteratively - get immediate results from inference API. You can also register your own model via REST API.
Build custom workflows and integrate them with any part of your data pipeline. Connect external storage, collaborate in real-time, label, manage, and push data externally in a few clicks.
Workflows is V7’s way of helping you structure your ML pipeline—from uploading your data, assigning roles, labelling and reviewing it, and training your models
Bring together all stakeholders - from annotators to data scientists and machine learning engineers, your team can collaborate in real-time in one unified platform. Assign user roles, spot data errors, and create Ground Truth faster
Solve any labeling task 10x faster, train accurate AI models, manage data, and hire pro labelers that care about your computer vision projects
Learn how world-class ML teams build AI products with V7
What I appreciate the most about V7 is flexible UI and API, responsive support, and active development of new features and bug fixes.
"I like the auto-segmentation feature. To me, that’s a nice AI feature that V7 took beyond the gimmick feature - it’s mature enough to be useful."
"We needed a tool that lets us keep the data in one place, annotate, and version it. Having found V7, we decided not to build the internal solution. "
We were looking for an annotation tool that would be much faster, and V7 sped up our labeling 9–10x compared to VGG. The appeal of using V7 is that it’s commercial off-the-shelf, very intuitive, and easy to use for non-technical people involved in our project.
"V7 did everything that we wanted—it enabled us to label videos in the way we needed, the turnaround time for new features was really fast, and the reviewing and sorting process was much better."
"We needed a tool that could do annotating and data versioning because we distribute our tools to farms, and we need to make sure that they have the same version of data for the same models. V7 met our needs."
Having accurately annotated datasets was crucial to catch the typical features of malignant melanoma. V7 lets us visualize the balance of this data across populations.
V7 is helping us manage a complicated, intricate, pixel-perfect labeling exercise. Their model-assisted labeling is the best around.
“Thanks to V7, the image annotation is 30% faster, but realistically, considering the whole process - transferring files and QA - we more than doubled the number of images we can do in the same span of time.”
Managing our data from one place is particularly important for us. Previously, our data was stored in many different formats and in different places. Having a single source makes our data more robust and also greatly reduces the development time for new algorithms, as the learning curve for developers is small.
"We use V7 to make our workflow for deep learning training and annotation streamlined and efficient. From the pathologist’s point of view, V7 turned out to be much easier to learn and use than other software - I can easily understand what I’m doing."
V7 is super sleek, intuitive, and easy to use. Within a couple of minutes, you're off to the races and can annotate quickly. The team is highly responsive and helpful.
"Visibility on metrics and annotators' work in V7 is very helpful to us, and it's something we didn’t have in our internal solution. The option to check past annotations and review the work is also valuable, along with V7’s ability to interactively define the workflows and the flexibility in task assignment."
Discover how other AI-first companies solved knowledge tasks at scale with V7
.png)
.png)
.png)
.png)
.png)
.png)
V7 supports image, video, and text data. The file formats you can use with V7 include: JPG, PNG, MP4, MOV, AVI, BMP, SVS, TIFF, DCM, ZIP, DICOM, NIfTI.
V7 offers three pricing plans: Team, Business, and Pro. The team plan starts at $5,000/year. For detailed pricing and feature overview see the V7 pricing page.
Medical image annotation involves labeling the medical imaging data such as X-Ray, Ultrasound, MRI, CT Scan, etc., for training machine learning models.
Yes. V7 works with a trusted network of partners and professional annotators who will help you turn your data into ground truth. Go to V7 Labeling Services to submit the form and we will send you a proposal within hours.
We offer in-app chat support and email technical support to all of V7 users. We will make sure to take good care of you and your team. You can get in touch with us at: support@v7labs.com.
