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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 Ango Hub?

Ango Hub serves as a comprehensive and quality-focused data annotation platform tailored for AI teams. Accessible both on-premise and via the cloud, it enables efficient and swift data annotation without sacrificing quality. What sets Ango Hub apart is its unwavering commitment to high-quality annotations, showcasing features designed to enhance this aspect. These include a centralized labeling system, a real-time issue tracking interface, structured review workflows, and sample label libraries, alongside the ability to achieve consensus among up to 30 users on the same asset. Additionally, Ango Hub's versatility is evident in its support for a wide range of data types, encompassing image, audio, text, and native PDF formats. With nearly twenty distinct labeling tools at your disposal, users can annotate data effectively. Notably, some tools—such as rotated bounding boxes, unlimited conditional questions, label relations, and table-based labels—are unique to Ango Hub, making it a valuable resource for tackling more complex labeling challenges. By integrating these innovative features, Ango Hub ensures that your data annotation process is as efficient and high-quality as possible.

Media

No images available

Media

Integrations Supported

Integrations Supported

AWS AI Services
Azure Blob Storage
Azure Databricks
Google Cloud AI Infrastructure
Snowflake

API Availability

API Availability

Has API

Pricing Information

Pricing not provided

Pricing Information

Free version allows users to invite up to 5 people and annotate 10k assets. Paid Cloud version allows for unlimited assets, with a charge for every 5 users. For on-premise installation contact us for pricing.
Free Version

Supported Platforms

SaaS

Supported Platforms

SaaS
On-Prem

Customer Service / Support

Not specified

Customer Service / Support

24 Hour Support

Training Options

Not specified

Training Options

Documentation Hub

Company Facts

Organization Name

EnFuse Solutions

Date Founded

2026

Company Location

United States

Company Website

tagi5.ai/

Company Facts

Organization Name

iMerit

Date Founded

2013

Company Location

Silicon Valley

Company Website

imerit.ai/products/ango-workflow-automation-by-imerit/

Categories and Features

Data Annotation

Not specified

Categories and Features

AI Fine-Tuning

Not specified

Artificial Intelligence

Chatbot
For Healthcare
For Sales
For eCommerce
Image Recognition
Machine Learning
Multi-Language
Natural Language Processing
Process/Workflow Automation

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
SDK
Supports Audio Files
Task Management
Team Collaboration
Training Data Management

Image Annotation

Not specified

LLM Evaluation

Not specified

RLHF

Not specified

Video Annotation

Not specified

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