The AI Data Engine to
 

Solve any labeling task 10x faster with an API for image annotation and dataset management

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Training data task assignmentTraining data quality review
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Workflow on V7
Powering the Machine Learning teams at
Paige AI
Simens Healthineers
Bayer
Insitro
Tractable

Manage your Datasets

Help your machine learning teams keep track of their most valuable assets. Ensure your team understands your labels and edge cases.

The CLI & SDK for AI Training Data

Perform actions on your assets via a CLI/SDK rather than the UI. Create, manage, export, and import your datasets and data conveniently with a single command.

CLI and SDK for AI Training on V7

Supporting all the formats you need

Upload your video data or ultra-high resolution images—browse and annotate them using one platform. V7 supports JPG, PNG, TIF, MP4, MOV, SVS, DICOM, and more.

Data formats list available on V7

Version control datasets

Stay on top of your annotation versions. Reference each model to a dataset version as your datasets keep growing.

Version control option on V7

Visualize, sort, and filter your data

Instantly preview all images and videos thanks to a highly efficient Elixir architecture. Filter by upload time, labeler, tag, class, or progress.

Search and filter features on V7

Annotate Any Visual Data

Create pixel-perfect annotations on any data format with class-agnostic, automated tools. Boost your annotation speed by up to 10x.

Auto annotating a car on V7

Pixel-perfect labels in one click

Create pixel-perfect polygon masks using V7's class-agnostic neural network — instantly and without prior training. All you need to do is click on object parts to either include or exclude them. Fine-tune your model once you gather enough training data.

Annotation types available on V7

All the annotation types your team will need

Easily annotate all Video, Image, and Text data. Choose from a variety of tools, such as polygons, brush, or bounding boxes. Solve any CV task from image classification to instance segmentation to object tracking and more.

Performance analytics on V7

Monitor labeler and model performance

Track the time spent, see how many annotations are created per minute, check the total number of labeled images, monitor accuracy, and more. No matter if you have 10 or 1,000 labelers.

Real-time collaboration on V7

Collaborate in real-time

Annotate images in collaboration with other users and add multiple labels to a single video or image simultaneously. Communicate in real time to make sure your labels are accurate and all team members know what the ground truth looks like.

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Add Any Model

Experience V7’s powerful model training and automated labeling capabilities. Use our pre-trained models or bring your own.

Combine models, humans, and data in composable workflows

Customize your workflows quickly and flexibly. Add annotations manually, include the model stage to automate parts of or the entire labeling process, decide when reviewers step in—see what works best for you.

Workflow building on V7

Train label-assistant models with AutoML

Turn your images or datasets into models on V7. At a click of a button.

Training models with AutoML on V7

Register any external model to use within your pipelines

If you have a repository of your own models, you can easily upload them to the V7 platform’s storage and keep them in order.

Running models on V7

All your team's models in one place, ready to use

Keep all your company models in one place. Deploy them for model-assisted labeling tasks or use them to train new AutoML models.

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Manage Humans in the Loop

Automate your workflows while making sure the right task gets assigned to the right person. Eliminate spreadsheets, data leaks, or quality control issues.

Annotators list with a Hire more labelers button at the bottom on V7

Professional on-demand labelers are a few clicks away

Entrust your training data to expert labelers. V7 gives you access to 5,000+ highly trained annotators who know the platform inside out. They’ll help you scale your project while following top-quality standards.

Expect review on V7 platform

Domain expert annotators that excel in your domain

Medical, scientific, agricultural, construction, or autonomous driving projects? You name it! We collaborate with experts from a variety of industries to ensure data accuracy and reliability.

Security standards on V7

Leading Security Standards

Working on sensitive data? V7 lets you assign tasks to specific labelers and make them only see the task at hand. Our platform is SOC2, HIPAA, and ISO27001 compliant.

Slack conversation of annotation projects team members

Fully Managed Projects

Cooperate with a dedicated V7 project manager. Design the most effective and efficient workflows and set your quality standards. The manager will see to it that all deliverables match your expectations.

the data engine

Manage your AI data in a single ML-Ops platform

Integrations

Connect to anything

Host data privately in your enterprise cloud storage. Send tasks to other ML-Ops platforms. Load datasets into your deep learning framework of choice in 1 step.

AWS
Snowflake
Google Cloud Platform
Azure Blob Storage
REST
Keras
Pytorch
Webhook
HTTPS
Weights & Biases
TensorFlow
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
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Hear it from our customers

“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."

"The API is very straightforward to use, so we can easily get data into our local computer system. Annotations are formatted in JSON, which is easier to parse. V7 also offers a lot of pre-trained networks that we can utilize."

What I appreciate the most about V7 is flexible UI and API, responsive support, and active development of new features and bug fixes.

"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."

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.

V7 is helping us manage a complicated, intricate, pixel-perfect labeling exercise. Their model-assisted labeling is the best around.

"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."

"V7 is really easy to use. It looks good and feels good. The other great thing is the customer support - bugs are fixed, email support is very fast, and feature requests are delivered as promised."

"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."

"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 lets us keep the data in one place, annotate, and version it. Having found V7, we decided not to build the internal solution. "

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.

Industry-Specific Tools

Industries building AI through V7

Find out whether your industry's image formats can be used to automate tasks through V7

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Gain control of your training data
15,000+ ML engineers can’t be wrong