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V7 Lab

AI document automation and training data platform for computer vision and LLM workflows.

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Intro

What is V7 Lab?

V7 (commonly referred to as v7labs or v7 labs) is an AI-powered platform designed to automate document processing and streamline dataset annotation workflows. The platform is divided into two primary solutions: V7 Darwin, which specializes in dataset annotation for computer vision and generative AI, and v7 go, which focus on document workflow automation and multi-modal data extraction. By providing structured, high-quality training data, the platform helps development teams prepare datasets to train object detection systems like a yolo model (and other yolo architectures), allowing engineers to optimize model performance and improve evaluation metrics such as the f1 score. Additionally, the platform structures multi-modal inputs to support diverse machine learning paradigms, including supervised training and self-supervised contrastive learning.

V7 Lab at a glance
Professional from $249/mo, Custom plans available184K monthly visitsPaid access

Category

AI Image RecognitionNo-Code&Low-Code
Best For

Best V7 Lab use cases by task, role, industry, and platform

These use cases show where V7 Lab fits best, ranked by fit score before popularity or pricing.

Data LabelingAnnotate text, images, and audio files to create high-quality training datasets for machine learning models.98Data AnnotationLabel, tag, and categorize text, images, and audio datasets to train machine learning models efficiently.98AI Training DataCollect, clean, label, and format diverse datasets to train machine learning models for specific business use cases.98Workflow AutomationMap processes, define triggers, connect tasks, and document outcomes for workflow automation.96AutomationConnect recurring steps, prepare rules, summarize outcomes, and reduce manual work across routine processes.95Data ExtractionData extraction organizes datasets, tables into cleaned tables, summaries during research, reporting.95Image AnnotationLabel, tag, and segment visual data like bounding boxes or polygons to prepare high-quality datasets for machine learning models.95Document AnalysisDocument analysis supports document review by organizing comments, sections, revisions, and important extracted details.95Process AutomationOffice and operations teams turn messages, documents into organized tasks, status summaries for administration, coordination.92Business AutomationMap repeated processes, draft rules, connect systems, and document outcomes for business automation.92
Pricing

V7 Lab Pricing Plans

Compare V7 Lab free options, V7 Lab paid pricing plans, and usage notes before you choose the best way to use this AI tool in 2026.

Professional from $249/mo, Custom plans available

$249 per month

Designed for growing teams ready to streamline and automate workflows. Includes up to 25k fields, 3+ seats, and in-app support.

Contact for Pricing

For large-scale usage, dedicated integrations, custom data retention, Bring Your Own API Key (BYOK), SSO/SAML, and support from a dedicated AI Solutions Engineer.

Pricing updated:Jun 11, 2026

Features

V7 Lab AI Features

AI-driven document workflow automation with reasoning steps for LLMsMulti-modal data extraction from PDFs, recordings, spreadsheets, and other formatsAI-assisted computer vision labeling utilizing SAM2 and Auto-Annotate technologiesOn-demand data annotation services with access to expert human annotatorsEnterprise-level security including SOC 2 Type II certification and end-to-end encryption
Pros & Cons

V7 Lab Pros and Cons

Pros

  • No-code interface allows quick setup for non-technical team members
  • Flexible support for multiple file formats and complex document layouts
  • AI-assisted annotation tools help reduce manual labeling hours
  • Robust security features ensure private data retention

Limitations

  • The Professional plan has hard limits on active fields and tokens
  • Enterprise features like SSO/SAML and dedicated SLAs require custom pricing plans

V7 Lab FAQ

Yes, V7 Darwin is designed to handle computer vision labeling workflows, making it straightforward to annotate images and videos for training a yolo model or other object detection frameworks.

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