V7

About V7

V7 is an AI training data platform that provides high-quality image and video annotations for computer vision models, utilizing AI-assisted labeling tools to enhance accuracy and efficiency. The platform addresses the challenge of slow and error-prone data labeling processes by streamlining workflows and enabling rapid deployment of training data.

```xml <problem> Training robust computer vision and generative AI models requires accurately labeled image and video data, but manual annotation is slow, expensive, and prone to errors, creating a bottleneck in AI development. Existing tools often lack the AI assistance and workflow automation needed to efficiently manage large datasets and diverse annotation tasks. </problem> <solution> V7 provides an AI-assisted data annotation platform designed to streamline the creation of high-quality training data for computer vision and GenAI applications. The platform combines automated labeling tools, customizable workflows, and expert annotation services to accelerate the data preparation process. By automating repetitive tasks and minimizing labeling errors, V7 enables teams to move from R&D to production faster while maintaining data privacy and security. </solution> <features> - AI-assisted labeling with tools like SAM2 and V7 Auto-Annotate to automate repetitive annotation tasks - Customizable workflows to manage complex annotation projects and diverse data types - Support for image annotation, video annotation, DICOM & NIfTI, RLHF & GenAI, and microscopy data - Multi-modal data extraction from PDFs, call recordings, pitch decks, spreadsheets, and other file formats - Integration with a network of 40,000 expert annotators for specialized training data needs - Enterprise-level security with end-to-end encryption and SOC 2 Type II certification - Granular permissions and transparent use of models to ensure data privacy and compliance - V7 Go for document workflow automation using LLMs </features> <target_audience> V7 targets AI research teams, data scientists, and machine learning engineers across industries like healthcare, finance, logistics, and manufacturing who need high-quality, accurately labeled data to train computer vision and generative AI models. </target_audience> ```

What does V7 do?

V7 is an AI training data platform that provides high-quality image and video annotations for computer vision models, utilizing AI-assisted labeling tools to enhance accuracy and efficiency. The platform addresses the challenge of slow and error-prone data labeling processes by streamlining workflows and enabling rapid deployment of training data.

Where is V7 located?

V7 is based in London, United Kingdom.

When was V7 founded?

V7 was founded in 2018.

How much funding has V7 raised?

V7 has raised 43280000.

Location
London, United Kingdom
Founded
2018
Funding
43280000
Employees
92 employees
Major Investors
Temasek Holdings, Radical Ventures

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V7

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Executive Summary

V7 is an AI training data platform that provides high-quality image and video annotations for computer vision models, utilizing AI-assisted labeling tools to enhance accuracy and efficiency. The platform addresses the challenge of slow and error-prone data labeling processes by streamlining workflows and enabling rapid deployment of training data.

v7labs.com20K+
cb
Crunchbase
Founded 2018London, United Kingdom

Funding

$

Estimated Funding

$20M+

Major Investors

Temasek Holdings, Radical Ventures

Team (75+)

No team information available.

Company Description

Problem

Training robust computer vision and generative AI models requires accurately labeled image and video data, but manual annotation is slow, expensive, and prone to errors, creating a bottleneck in AI development. Existing tools often lack the AI assistance and workflow automation needed to efficiently manage large datasets and diverse annotation tasks.

Solution

V7 provides an AI-assisted data annotation platform designed to streamline the creation of high-quality training data for computer vision and GenAI applications. The platform combines automated labeling tools, customizable workflows, and expert annotation services to accelerate the data preparation process. By automating repetitive tasks and minimizing labeling errors, V7 enables teams to move from R&D to production faster while maintaining data privacy and security.

Features

AI-assisted labeling with tools like SAM2 and V7 Auto-Annotate to automate repetitive annotation tasks

Customizable workflows to manage complex annotation projects and diverse data types

Support for image annotation, video annotation, DICOM & NIfTI, RLHF & GenAI, and microscopy data

Multi-modal data extraction from PDFs, call recordings, pitch decks, spreadsheets, and other file formats

Integration with a network of 40,000 expert annotators for specialized training data needs

Enterprise-level security with end-to-end encryption and SOC 2 Type II certification

Granular permissions and transparent use of models to ensure data privacy and compliance

V7 Go for document workflow automation using LLMs

Target Audience

V7 targets AI research teams, data scientists, and machine learning engineers across industries like healthcare, finance, logistics, and manufacturing who need high-quality, accurately labeled data to train computer vision and generative AI models.

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