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What is Tagi5?

Tagi5, created by EnFuse Solutions Ltd., serves as a sophisticated platform designed for data annotation, seamlessly combining the labeling of images, documents, and videos into a unified and intelligent workspace. By leveraging AI-assisted annotation along with essential features such as quality review workflows, optical character recognition (OCR), masking, and flexible export options, it enables organizations to generate high-quality training data more efficiently and on a larger scale. Specifically designed for AI teams, Tagi5 harmoniously integrates platform features, human talent, and operational workflows to streamline the entire process of data sourcing, annotation, quality assurance, and delivery into a single, comprehensive solution. This cutting-edge methodology not only boosts productivity but also guarantees that the data adheres to the stringent standards necessary for successful AI training, ultimately making the entire data handling process more effective. With Tagi5, teams can expect improved collaboration and faster turnaround times, leading to enhanced project outcomes.

What is Alegion?

An advanced labeling platform designed for various stages and types of machine learning development is at your service. By utilizing a collection of top-tier computer vision algorithms, we can swiftly identify and categorize the content within your images and videos. Traditionally, creating thorough segmentation data has been a labor-intensive endeavor; however, our machine assistance can enhance productivity by up to 70%, ultimately conserving both time and financial resources. We harness machine learning to suggest labels that facilitate and expedite human labeling processes, employing computer vision models that can automatically detect, localize, and classify elements in your images and videos before passing the task to our skilled workforce. This approach to automatic labeling not only decreases labor costs but also allows annotators to focus on the more intricate aspects of the annotation process. Furthermore, our video annotation tool is engineered to natively support 4K resolution and lengthy videos, incorporating cutting-edge features such as interpolation, object proposal, and entity resolution, ensuring a comprehensive and efficient annotation experience. With our platform, you can achieve higher accuracy and efficiency in your machine learning projects.

Media

No images available

Media

Integrations Supported

Integrations Supported

Amazon S3
Azure Storage
Google Cloud Storage

API Availability

API Availability

Has API

Pricing Information

Pricing not provided

Pricing Information

$5000
Hourly rates for Control SaaS and Alegion Managed Platform offerings. Hourly, per project, and per annotation pricing model options for Fully Managed Labeling Services.
Free Trial Offered?

Supported Platforms

SaaS

Supported Platforms

SaaS

Customer Service / Support

Not specified

Customer Service / Support

Standard Support
Web-Based Support

Training Options

Not specified

Training Options

Documentation Hub
Webinars
Online Training

Company Facts

Organization Name

EnFuse Solutions

Date Founded

2026

Company Location

United States

Company Website

tagi5.ai/

Company Facts

Organization Name

Alegion

Date Founded

2014

Company Location

United States

Company Website

www.alegion.com

Categories and Features

Data Annotation

Not specified

Categories and Features

Computer Vision

Blob Detection & Analysis
Image Processing
Multiple Image Type Support
Reporting / Analytics Integration

Data Annotation

Not specified

Data Labeling

Human-in-the-loop
Labeling Automation
Labeling Quality
Performance Tracking
Polygon, Rectangle, Line, Point
Supports Audio Files
Task Management
Team Collaboration
Training Data Management

Data Preparation

Data Transformation
Machine Learning
Visual User Interface

Image Annotation

Not specified

Machine Learning

Natural Language Processing (NLP)

Natural Language Processing

Named Entity Recognition
Part-of-Speech Tagging
Sentence Segmentation

Video Annotation

Not specified

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