Data labeling for Frontier Models. Lightning-fast, expert-driven.

Create ground truth 10x faster without errors.

Manage expert labelers with AI-assisted annotation and review.

Data labeling services.

On-demand and world class. From healthcare videos to driving footage, V7's professional workforce accelerates your AI development.

Integrations.

SDK, API, and storage. Integrate V7 seamlessly into your existing infrastructure using API keys and the Darwin-py SDK.

Custom workflows.

Collaborate in real-time. Real-time collaboration, task management, automated quality assurance, and seamless integration with external tools.

AI-assisted labeling.

Speed meets accuracy. Accelerate labeling with AI-powered tools that deliver precision and scalability. Automate your annotation process while keeping quality in check.

Annotation tools.

For all data types. Turn files in any modality into high-quality training data with our comprehensive annotation toolkit.

Annotate any dataset with speed and accuracy

For many AI teams, creating high-quality training datasets is their biggest bottleneck. Annotation projects often stretch over months, consuming thousands of hours of meticulous work. V7 can speed up data annotation 10x, turning a months-long process into weeks. Use intuitive interface and AI-assisted tools to turn complex labeling tasks into a few simple clicks and adjustments. Work with any size dataset and file type, from videos, PDFs, and architectural drawings to specialized medical formats like SVS or DICOM.

AI-assisted data labeling

Label data at lightning speed with V7 Auto-Annotate and SAM2. Segment complex objects like lesions in CT scans and items on assembly lines with high accuracy. Achieve expert level segmentation across diverse domains, regardless of industry.

Auto-track for video

Track objects across selected time ranges in videos. Automatically follow instances and mark in-and-out of view situations. Streamline video annotation for tasks like AI-assisted surgeries, retail shrinkage prevention, or sports analytics.

Label similar objects

Pick one object and find similar ones automatically. Speed up repetitive annotation problems like preparing training data for cell counting models or product identification on shelves. Reduce manual effort in large-scale labeling projects. Reduce human errors caused by fatigue and monotony.

Model in the loop

Integrate external or out-of-the-box models to pre-label your data or detect quality issues. Compare performance between human labelers and AI models in blind tests. Connect models to your ML pipeline and improve your annotation process and model accuracy.