WORKFLOWS

Connect Models and Humans into Workflows

Plot the best routes for your training data. Ensure the quality and cut down on AI model delivery times through automation

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ML pipeline

Build robust ML pipelines, deploy reliable AI faster

Use a model to label more data
Send edge cases back to be labeled
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Collect Data
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Label Data
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Train Your Model
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Manage Data
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Deploy AI
Workflow stages

All the flexibility you need for your data labeling projects

V7 offers you eight workflow stages you can arrange, connect, and loop in any way you need

Dataset
The dataset stage is a starting point for any data workflow. Datasets can be browsed and exported for training.
Learn more about dataset management ->
Annotate
The annotation stage is where the bulk of annotation work happens, and you get access to all V7 annotation tools. You can add multiple annotation stages and assign different users to complete them.
Learn more about auto annotation ->
Consensus
The consensus stage lets you compare independent annotations. You can decide what level of overlap between different annotations determines whether they get approved or rejected.
Model
The model stage lets you connect an AI model to annotate images automatically. You can import a pre-trained public model (e.g., COCO), your own model, or use V7 to train computer vision models from scratch.
Learn more about model management ->
Review
In the review stage, you decide who is responsible for reviewing the annotation process. You can add multiple review stages in various parts of the workflow.
Webhook
The webhook stage triggers an automated event. For example, a webhook can trigger Slack notifications when a reviewer rejects an annotation. You can use the stage in combination with Zapier to turn webhooks into Zaps.
Code
In the code stage, you can add custom code snippets to your workflows. The feature is currently in development.
Logic
Logic stage lets you control how your data flows by checking for specific tags or annotations. Based on these, it can send data to other stages. You can add multiple rules to logic stages, and they are useful in automating quality control. The feature is currently in development.
Complete
This is the final stage of any workflow. You can define what “complete” means to you—for example, it may mean that your data is ready for export or model training.
Archive
This is where you can keep all images whose annotations don’t meet a certain accuracy threshold
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 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.

Ryan Watson
Segmentation Manager at Intelligent Ultrasound
Try V7 Now->
Ryan Watson
Segmentation Manager at Intelligent Ultrasound
Benefits

Develop production-ready AI in hours, not weeks

The easiest low-code experience to help you train and ship performant AI

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Full visibility over your data

Gain insights into your data at every stage of its journey. Spot bottlenecks and resolve them without communication overhead.

Workflow templates

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.

Automate data pipelines

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.

No-code required

Drag and drop stages to connect them into custom workflows. Leverage no-code interface and complete your AI projects without dev help.

Train models iteratively

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.

Integrate with any ML pipeline

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.

WORKFLOW types

Custom workflows for any ML project

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

Simple data workflow
Dataset
Annotate
Complete
Complex data workflow
Review
Model
Consensus
Webhooks
Real-Time collaboration

Built for teams of all sizes

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

the data engine

Develop your AI training data in a single ML-Ops platform

Solve any labeling task 10x faster, train accurate AI models, manage data, and hire pro labelers that care about your computer vision projects

Reviews

Hear it from our customers

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."

API

Built by ML engineers, for ML engineers

Discover how other AI-first companies solved knowledge tasks at scale with V7

Tools for every stack
Leverage the REST API, integrate with the Python library, or quickly apply mass actions via CLI
Prebuilt integrations
Load datasets into Pytorch, connect your cloud storage, and integrate MLOps tools
Data
Quality
Settings
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Frequently
Asked Questions
Reach out to our support team or contact us for further questions
What type of data does V7 support?

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.

What pricing plans do you offer?

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.

What is medical image annotation?

Medical image annotation involves labeling the medical imaging data such as X-Ray, Ultrasound, MRI, CT Scan, etc., for training machine learning models.

Does V7 offer labeling services?

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.

What type of support does V7 offer?

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.

Gain control of your training data
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